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Southern Polytechnic College of Engineering and Engineering Technology 2023-2024 Projects

Click here to return to the main project listings page. Questions: Email our@kennesaw.edu.

  • 2023-2024 First Year Scholars: Justin Chen and Alhagi Kebbeh

    • Several recycled waste materials such as plastic, rubber, glass, sewage sludge ash (SSA), fly-ash (FA), scrap metals (slags), etc. are abundant in the waste stream that go to landfill and occupy the valuable landfill space. Research shows that these waste materials are used in several applications such as manufacturing mortar, concrete, and bricks. During the lifetime of these materials' usage, heavy metals and other chemicals can leach out and contaminate the water and soil. The heavy metal and other chemical contents in these waste materials are important to quantify to understand the future impact on water and soil pollution.

      In the proposed project, several recycled waste materials will be collected from local recycling facilities and toxicity characteristics of leaching procedure (TCLP) tests following USEPA 1311 method will be performed to quantify the metal concentrations. Fourier Transform Infrared Spectroscopy (FTIR) test will be performed to quantify other chemicals. 

    • Undergraduate civil and environmental engineering students will be trained and guided as to how to do the literature review, use the equipment to conduct experiments, and generate data. Finally, the students will be guided to analyze and interpret data, draft conference articles and/or posters for presentation.

    • 1. Attend weekly progress meeting.
      2. Collect recycled waste materials from local recycle facilities as necessary.
      3. Generate data through laboratory experiments.
      4. Analyze and interpret data as necessary for inclusion in the reports and/or poster.

    • Face-to-Face

    • Dr. M.A. Karim, mkarim4@kennesaw.edu
      Dr. Younguk Seo, yseo2@kennesaw.edu

  • 2023-2024 First Year Scholars: Bryan Bae, Katherine Gurno, Sydney Tarman, and Justin Zhu

    • Biodegradable soil moisture sensors could improve sustainability and life cycle impacts at field-scale while providing low-cost, low-maintenance alternatives for agricultural operations. These sensors can help in the optimization of water applications in irrigated cropping systems which ultimately reduces the water footprint but also the carbon footprint of agricultural operations.

      The objectives of this research will be to

      1. perform a life cycle assessment (LCA) of agricultural operations to produce Solanum lycopersicum (Roma Tomatoes)
      2. quantify the degradation of soil moisture sensor component materials
      3. determine the effects of material degradation on Solanum lycopersicum growth and development, and
      4. assess outcomes from instructionally designed undergraduate research experiences on undergraduate student researchers’ motivation using the MUSIC Model.

    • Students will:

      1. Learn how to conduct a Literature Review
      2. Learn the basics of conducting a Life-Cycle Assessment
      3. Learn how to setup Bench-scale Laboratory Experiments
      4. Perform preliminary data collection and statistical analysis 

    • Students will work 5 - 7 hours weekly.

      These hours will consist of a weekly 30-minute research team meeting. The rest of the time will be spent doing experimental setup (e.g., planting, watering, and nutrient administration), data collection (e.g., weighing of plant biomass and sensor components), and literature searches.

    • Face-to-Face

    • Dr. Roneisha Worthy, rworthy@kennesaw.edu

  • 2023-2024 First Year Scholars: Cameron Ramsey

    • The development of carbon-neutral construction materials and the transformation from over-exploitation to sustainable development has been prioritized in the construction industry as the mass production of concrete has caused enormous environmental and ecological issues. 3D concrete printing (3DCP) involves the process of assembling materials by printing a series of single filament stacks to build 3D models. It has gained popularity in the construction industry as it makes the core construction process faster, cleaner, and more cost-effective.

      However, the use of high flow materials for 3DCP can result in poor performance due to the separation of materials, the generation of a large volume of voids, and the reduction in interlayer adhesion, which collectively put 3DCP buildings at risk of failure when exposed to chloride ions at certain temperatures and moisture contents. To maximize the advantages of 3DCP, especially for roadways and marine infrastructure, this study develops new 3DCP mixes of eco-filaments sourced from local industrial waste. The durability of the 3DCP mixes is then evaluated in a chloride-loaded environment, where chloride intrusion into the near surface pores of the concrete is focused as an underlying damage mechanism. Since chloride ingress is attributed to chloride binding with cement hydrates at microscale, understanding cement hydration is the key to characterizing the physicochemical properties and complex interactions with chloride for durable 3D printed concrete.

      The proposed research program aims at:

      1. investigating the incorporation of low carbon embodied materials for 3DCP
      2. correlating macroscopic properties with microscopic properties through laboratory experiments
      3. evaluating the impact of chloride ingress on the performance of 3D printed concrete.

      The findings of this research will advance our understanding of cement hydration and its interactions with chloride and lead to an optimum design method for the sustainable and durable 3DCP construction.

      1. Gain experience in conducting scientific investigations, literature reviews, and data analyses.
      2. Acquire specialized knowledge in construction materials, sustainable building practices, and concrete technology.
      3. Design materials that can address the limitations of conventional high flow materials and contribute to sustainable construction practices.
      4. Learn laboratory techniques and data analysis methods relevant to their research.
      5. Develop effective communication skills as they share their findings, progress, and ideas with their peers and mentors.
      6. Present their work at conferences or publish their results in academic journals.
      1. Attend weekly progress meeting.
      2. Collect recycled waste materials from local recycle facilities.
      3. Generate data through laboratory experiments.
      4. Analyze and interpret data as necessary for inclusion in the reports and/or poster.

    • Face-to-Face

    • Dr. Youngguk Seo, yseo2@kennesaw.edu

  • 2023-2024 First Year Scholars: Frank-Cedric Kadjo and Kiara O'Neal

    • The safety, reliability, and longevity of transportation infrastructure are critical for maintaining efficient and effective transportation networks. Bridge inspections are an essential part of this process, ensuring that potential issues are identified and addressed in a timely manner. Traditional bridge inspection methods, however, can be labor-intensive, time-consuming, and costly. Furthermore, these methods often require the temporary closure of bridges, causing disruptions to traffic flow and imposing additional burdens on communities. In response to these challenges, the use of drones and computer vision techniques for bridge inspection has emerged as a promising alternative. By leveraging these advanced technologies, inspection processes can be made more accurate, comprehensive, and efficient, while also reducing costs and minimizing traffic disruptions. The development of an automated bridge inspection framework, which combines drone-based image acquisition with sophisticated computer vision algorithms, has the potential to revolutionize the way bridge inspections are conducted, ensuring the safety and longevity of critical transportation infrastructure.

      The proposed project aims to create an automated bridge inspection framework that leverages drone technology and state-of-the-art machine learning techniques for the precise and efficient detection of various defects, including cracks and other structural issues, on bridge decks. This framework will not only streamline the inspection process, but also provide infrastructure managers with a detailed understanding of the bridge's condition, thus promoting better decision-making regarding maintenance and repair activities. By adopting this advanced framework, transportation authorities can improve the safety, reliability, and longevity of their infrastructure assets while minimizing costs and disruptions associated with traditional inspection methods.

      • Grasp practical aspects of conducting research.
      • Acquire skills in drone operation and machine learning techniques.
      • Improve critical thinking and problem-solving abilities.
      • Gain interdisciplinary knowledge in civil engineering, computer science, and data analysis.
      • Refine teamwork, communication, and conflict management skills.
      • Experience cutting-edge technologies in drones and computer vision.
      • Understand challenges and solutions in infrastructure maintenance.
      • Conduct literature reviews to understand current practices in bridge inspection.
      • Operate drone technology to gather data from bridge surfaces.
      • Implement machine learning techniques to analyze acquired images.
      • Develop and refine algorithms for precise defect detection.
      • Document project processes and findings in a research log.
      • Prepare presentations to share project updates and results.

    • Hybrid

    • Dr. Da Hu, dhu3@kennesaw.edu

  • 2023-2024 First Year Scholars: Collin Gregg, and Chrisley Licona

    • The Bipartisan Infrastructure Law (BIL) facilitates the investment of $135 million for the rapid development of public electric vehicle (EV) charging infrastructure in Georgia over the next five years (National Electric Vehicle Infrastructure (NEVI) Formula Program). As EV charging stations become more accessible and prices continue to drop, the use of EVs will increase steadily. With the advancement of battery technology, electric vehicle drivers will also travel more and longer distances at a lower cost for fuel and maintenance.

      This project aims to estimate the amount of electrical energy consumed by EVs from the power grid and the resulting increase in air pollution emissions from non-renewable energy power plants in Georgia. We will use the MOtor Vehicle Emission Simulator (MOVES) and the National Renewable Energy Laboratory (NREL) Cambium database to calculate the rise in energy consumption and air pollution emissions as the adoption rate of EVs increases over time. First-Year Scholars will have the opportunity to work closely with graduate students on this research project and potentially contribute as co-authors to the resulting research papers.

      • Enhance your knowledge on electric vehicle technology
      • Study the fundamentals of electrical energy consumption models
      • Use MOVES3.1 to generate simulation results
      • Analyze the data retrieved from NREL Cambium
      • Interact with graduate students on the research endeavor
      • Collaborate on the resulting research papers
      • Attend the Biweekly meetings
      • Complete the assigned tasks 

    • Hybrid

    • Dr. Mahyar Amirgholy, mahyar.amirgholy@kennesaw.edu

  • 2023-2024 First Year Scholars: Caleb Ludlam and Joseph Painter

    • The primary goal of this research is to identify and evaluate innovative strategies to minimize cement consumption and integrate landfill waste, specifically waste glass and plastics, into concrete design mixes. In a broader perspective, the project aims to advance sustainable practices within the construction industry, focusing on recycling and repurposing waste materials.

      The construction sector contributes significantly to global waste and emissions. Thus, promoting eco-friendly and sustainable practices in this domain is imperative. This research project embarks on an initiative to reduce environmental burdens associated with conventional construction methodologies. A secondary focus of the project is to develop a net zero manufacturing process that utilizes city waste wood, simultaneously reclaiming biochar for potential incorporation into concrete and wallboard designs.

      Integral to the research process, first-year undergraduate students will engage hands-on in various research activities. They will be involved in:

      • Chemical Composition Testing: Assessing the chemical composition of concrete mixes, especially when integrated with alternative supplementary cautious materials.
      • Physical Properties Examination: Conduct experiments to analyze and determine the physical properties of the newly developed concrete. This helps in understanding the concrete's strength, durability, and feasibility for real-world applications.

      The potential impact of this research is not limited to just the construction industry but extends to the academic realm. We are eager to collaborate with academic professionals passionate about sustainability. The symbiotic relationship aims to facilitate joint grant proposals, further research, and impart the significance of material reuse to future generations.

      This project stands as a testament to the transformative potential of innovative and sustainable construction practices. It aims to provide invaluable hands-on research experience to first-year undergraduate students and further the cause of environmental sustainability in construction.

    • After participating in this project, students will be able to:

      • Recall key components of traditional concrete.
      • Explain the importance of sustainable construction practices.
      • Conduct basic tests on concrete samples.
      • Compare properties of traditional vs. sustainable concrete.
      • Assess the effectiveness of waste-integrated concrete mixes.
      • Design new methods for integrating waste into concrete.
      • Mix and label concrete batches, varying the landfill waste components.
      • Regularly conduct physical and chemical tests on concrete samples.
      • Review test results, noting the impact of different landfill materials.
      • Attend weekly team briefings to share findings.
      • Ensure lab equipment is accurate and ready for tests.
      • Maintain a weekly log of activities and test results.
      • Ensure all activities adhere to safety protocols.
      • Participate in occasional training as required.

    • Hybrid

    • Dr. Metin Oguzmert, moguzmer@kennesaw.edu 

  • 2023-2024 First Year Scholars: Negin Javaheri, Caleb Oswalt, Kyle Vipperman, and Trinity Walker

    • This undergraduate research project is both simple and innovative, making it an attractive opportunity for Civil, Mechanical, and Mechatronic students. Participating in this research program will enable these students to establish a strong foundation for essential courses such as Statics, Strength of Materials, Structural Analysis, and Machine Design, among others.

      What sets this program apart is that students can achieve this without the need to grapple with complex equations. Instead, they will enhance their perspective and comprehension of various structures and mechanical frames, referred to as 'Systems' henceforth, during their research activities. This will help them appreciate the remarkable behavior of Systems and uncover the fundamental laws of physics that govern them. This approach revolves around the concept of load path, centric modeling, and a  focus on the connections of members within a System, as well as its supports. Not only does this approach enhance students technical knowledge, but it also equips them with a forward-thinking perspective on engineering principles.

      Structures and mechanical frame systems are developed through two major stages: analysis and design. To navigate these stages, a System must be modeled and simplified to a certain extent. This modeling need not replicate the exact nature of the System.

      Research students in this program will first familiarize themselves with the overall behavior of Systems by observing and photographing numerous examples. They will then engage in discussions with the professor during their weekly meetings. Data will be collected through observations of Systems on both the KSU and Marietta campuses, as well as other locations. Students will learn to create a computerized model of one of the systems using user-friendly finite element software. Over the course of the research period, a team of three students will collaborate on this process, resulting in individual poster presentations for each student, each focusing on a different System. These presentations will cover the load path, connections, supports, and simplification in modeling. Ultimately, students and the professor will present their findings in a conference or journal paper, highlighting two significant aspects of the research program: 1) the students' learning process from an educational standpoint, and 2) the research findings regarding the real behavior of Systems, taking into account load path, connections, supports, and modeling.

    • At the end of the project, students should be able to:

      • Comprehend the behavior of structural and mechanical frame systems from different aspects, including load path, connections and supports.
      • Develop an awareness and understating of the engineering systems that they come across in their daily life.
      • Articulate how their research study makes a contribution to their academic field
      • Define the terminology associated with research and theory in their field
      • Learn how to conduct literature review of past research studies in their research project
      • Collect, analyze, and interpret data for a research study
      • Work effectively as part of a team
      • Write a research paper 
      • Make a computerized model of the structure
      • Present their research/creative activity to an audience (e.g., poster, oral presentation, performance, display)
      • Reflect on their research project by writing a brief report at the end of their program.

    • Student weekly activities varies from week to week but involves the following activities:

      • Study the structural behavior from basics and develop their understanding  
      • Conduct literature review step by step and present to the professor in the meeting
      • Make observations and collect data of the Systems during their daily activity 
      • Analyze data and compare with the theory.
      • Become familiar with, and practice on the software to analyze the Systems.
      • Prepare an organized weekly report that can be used in their final paper.

    • Students will work on this project in hybrid form with majority of the work as face-to-face.

    • Dr. M. Jonaidi, mjonaidi@kennesaw.edu 

  • 2023-2024 First Year Scholars: Anielle Lenzer and Mikela Zuniga

    • The number of fatal motor vehicle-related crashes in the state of Georgia has increased rapidly in recent years. The economic cost associated with these crashes is in the range of billions of dollars every year. During the last five years from 2018 to 2022, there were 7,974 fatal crashes in Georgia and as a result, 8,636 Georgians have lost their lives. While we promote walking as a mode of transportation for short trips due to several reasons, the balance between the traffic flow and pedestrians needs to be maintained. However, unfortunately, during the last five years, 1,414 Georgians have lost their lives as pedestrians. In addition, 9,938 pedestrians have also been injured as a result of being involved in motor vehicle crashes. 

      As functioning adults, we all are pedestrians at some point during each day, and therefore this is an important topic for everyone. This study will therefore use crash data from GA in relation to pedestrian crashes and apply the commonly used statistical methods to identify the critical factors associated with the high number of fatal and injury crashes involving pedestrians. Crash data related to the proposed study will be acquired from the Georgia Department of Transportation and the detailed information gathered will include pedestrian characteristics such as age, gender, walking/driving under the influence, etc., and crash characteristics such as time and day, environmental factors at the time of the crash, level of speeding by the driver, type of the roadway, cause of the crash, movement at the time, location of the crash, etc. to name a few. Various characteristics will be studied and analyzed to identify the risk factors associated with pedestrian crashes. These will assist the First-Year Scholar in identifying the measures that would be helpful in reducing the number and severity of pedestrian crashes in GA so that the highway safety of all road users could be improved. 

    • Upon the completion of the project, the student will:

      • Understand the basic concepts in conducting research in the broad area of engineering
      • Understand how a literature review is conducted
      • Learn about basic data analysis practices
      • Understand how research findings could be derived by analyzing data
      • Be familiar with how research could be used to provide guidance on how pedestrian safety could be improved.
      • Educate themselves and others about the importance of good highway safety practices and the economic benefits associated with reducing pedestrian crashes

    • The following are the major tasks the student will engage in depending on the stage of the project.

      • Conduct a literature review about pedestrian safety and understanding the general issues and concerns.
      • Gather data related to pedestrian crashes in Georgia for the last five years.
      • Learn basic statistical methods that could be applied to analyze crash data.
      • Apply the most suitable methodology to analyze pedestrian crash data and identify the critical factors affecting the safety of pedestrians.
      • Write down the activities completed, and record the time spent working on the project.
      • Write an abstract and participate in the symposium.

    • Hybrid. The student is expected to meet face-to-face once a week for direction and discussion on the research/academic progress and work on their own prior to the next in-person meeting. 

    • Dr. Sunanda Dissanayake, sdissan1@kennesaw.edu 

  • 2023-2024 First Year Scholars: Annie Solomon

    • A Software Defined Radio (SDR) is a radio transceiver that is primarily defined in software. It allows radio engineers and researchers to easily control the hardware and implement and configure the physical layer in software. SDRs have been used in many scientific platforms to implement, test, and study different wireless technologies and protocols. In this project, we explore the 5G waveform generation function of the MATLAB 5G Toolbox to generate different uplink-downlink transmission frames.

      The 5GNR (5G New Radio) 'knobs' include the bandwidth (BW), the physical resource block (PRB) allocation within the BW, the time slot occupation, the numerology, and the number of transmission layers, and the transmit (Tx) power. The generated waveform is transmitted over the air (OTA) using the GNU Radio software framework in conjunction with Universal Software Radio Peripheral (USRP) or other commercial SDR hardware.

      In the proposed work, two SDRs are used to implement the test bed's transmitter and receiver sides. Each SDR is connected by USB 3.0 to a GNU Radio Companion computer. The transmitter and the receiver GNU Radio flowgraphs have a built-in spectrum analyzer (SA) block to visualize the fast Fourier transform of the signal for spectral analysis. We use the 5G Toolbox because of its flexibility to customize the uplink and downlink 5G NR transmission that complies with the 3GPP specifications. In addition, we use another MATLAB function to convert the in-phase and quadrature (IQ) samples to binary points for use with GNU Radio. GNU Radio is a free and open-source software development toolkit that provides the mechanisms and sample signal processing blocks to implement radios in software. It is compatible with low-cost SDR hardware to enable RF transmission.

      Furthermore, it has a graphical user interface—GNU Radio Companion—to assemble radios by connecting blocks. Moreover, we use a Software Defined Radio (SDR) and P21XXCSR-EVB Energy Harvesting module (existing) to conduct experiments on RF energy harvesting from the SDR transmissions. Specifically, we are interested in obtaining insight into joint communication and RF energy harvesting, aiming to transmit as much information as possible under the constraints of providing sufficient RF energy for the receiving device to operate. Experiments that will enable our insights into this problem include comparing communication waveform designs, comparing power emission via USRP, and the effect of environmental conditions like separation distance, presence of nearby in-band transmissions, and other factors. 

    • Most radios today use software-defined radio (SDR), where at least one of the traditionally analog radio functions is performed in the digital domain.

      • All students need to understand what is occurring inside an SDR receiver. This research familiarizes the student with the installation, operation, and analysis of an SDR radio and further extends the use of SDR in a novel application for the upcoming 2023-2024 SDR Challenge Academic Year Invite

      Increasingly, more radios are using software-defined techniques in lieu of older hardware methods. Whether the radio is commercial, consumer, or military most feature an SDR architecture. That means the receiver takes the incoming analog radio signal with its modulation and digitizes it in an analog-to-digital converter (ADC). The digital data representing the signal and the information it carries is stored in memory. Then a processor executes one or more digital signal processing (DSP) algorithms that implement the equivalent of the analog functions like filtering, demodulation, mixing, and decompression. The DSP may be performed with an embedded DSP-type controller or the standard kind with DSP instructions. The received signal is then recovered and sent to amplifiers and speakers or headsets. In some receivers, the normal front panel of the radio is replaced by a software user interface that emulates the frequency display, tuning, and other controls.

      • In this research, a modern SDR receiver will be set up and used, and analyze its architecture. It will then be used to transmit novel data.
        • You must install the software on your PC and apply Matlab/ Python programming. You will connect the radio to an antenna and a PC, then use the software user interface to tune and listen to stations. The receiver can receive normal AM radio broadcasts, shortwave stations, and amateur radio transmissions. It can demodulate AM, SSB, and CW (continuous wave code) signals.

      Furthermore, it has a graphical user interface—GNU Radio Companion—to assemble radios by connecting blocks. Moreover, we use a Software Defined Radio (SDR) and P21XXCSR-EVB Energy Harvesting module (existing) to conduct experiments on RF energy harvesting from the SDR transmissions. Specifically, we are interested in obtaining insight into joint communication and RF energy harvesting, aiming to transmit as much information as possible under the constraints of providing sufficient RF energy for the receiving device to operate.

      • Experiments that will enable our insights into this problem include comparing communication waveform designs, comparing power emission via USRP, and the effect of environmental conditions like separation distance, presence of nearby in-band transmissions, and other factors.

    • There are many high-impact situations where there is loss of telecommunication, for example natural disasters such as hurricanes and places where conventional telecommunication infrastructure is damaged such as in Ukraine, currently. In these cases, software definable, rapid deployable wireless communication systems are urgently needed.

      Our students will conduct high-impact research to solve crucial telecommunication problems, develop soft and entrepreneurial, and networking skills. We target external grants and industry support. We also prepare the students to use the analytical approach of an engineer, be able to integrate software, hardware and communication systems, and network infrastructures, and develop proof-of-concept projects related to future telecommunications.

      The students will develop essential articulation skills as we plan to present the work in seminars and other undergraduate symposiums. 

    • Hybrid

    • Dr. Sumit Chakravarty, schakra2@kennesaw.edu

  • 2023-2024 First Year Scholars: Mustafa Raza, Anish Sankuratri, and Mason Snyder

    • Background
      The research on next-generation energy storage devices has garnered significant attention recently, driven by the increasing demand for high-performance energy storage systems in various applications, including electric vehicles, biocompatible medical devices, consumer electronics, etc. Among the forefront candidates, lithium-ion batteries have gained substantial interest due to their promising capabilities. However, the current battery technology still utilizes flammable organic liquid electrolyte, which makes them susceptible to fire incidents when short circuit happens under extreme conditions (such as collisions, high temperatures, etc). Furthermore, the inadequacy of current battery technology in meeting the escalating energy demands has necessitated the exploration of alternative anode materials. By replacing conventional carbon-based anodes with Li-metal anodes, it becomes possible to optimize energy density and address the growing energy requirements effectively.

      Method and objective
      The project will employ a series of experimental techniques to synthesize and thoroughly characterize the novel solid electrolyte developed in our lab, as well as investigate the interfaces between the solid electrolyte and the anode and cathode materials. In addition, modeling techniques will be employed to complement the experimental observations and facilitate a comprehensive analysis of the underlying mechanisms governing charge transport behaviors in the all-solid-state lithium-metal battery system.

      The project encompasses two primary objectives. Firstly, it aims to develop an innovative and high-performance solid electrolyte through the application of cost-effective roll-to-roll printing and polymerization techniques. Secondly, it aims to achieve a comprehensive understanding of the charge transport behavior across the interfaces. Through these endeavors, the aim is to minimize charge transfer resistance inside the solid electrolyte and across these interfaces, leading to a substantial enhancement in overall battery performance.

      All the materials will be developed in our lab located in the Engineering Technology Center (Q building). The comprehensive characterization will be done using equipment located in our lab and other necessary shared facilities at Kennesaw State University. 

    • I expect the students to learn and develop the followings skills-based outcomes and techniques:

      1. Develop scientific research method and strict research attitude
      2. Define the terminology associated with research and theory in their field
      3. Describe past research studies in their field of study
      4. Articulate how their research study makes a contribution to their academic field
      5. Be able to find research resources through reading research papers
      6. Be able to perform the basic material synthesis procedures
      7. Be able to perform the basic material characterization techniques
      8. Be able to perform the basic battery characterization techniques
      9. Become familiar with testing and data collection, especially for Li-ion batteries
      10. Become familiar with curve fitting using linear and nonlinear regression
      11. Exhibit a basic understanding of physical models and mechanisms related to Li-ion battery failure
      12. Analyze, synthesize, organize, and interpret data from their research study
      13. Work effectively as part of a team
      14. Write a research paper
      15. Present their research/creative activity to audience (e.g., poster, oral presentation, performance, display)
      16. Articulate what it means to be a scholar in their academic field
      17. Articulate the ways in which their research participation helps prepare them for graduate school or career
      18. Describe appropriate professional conduct (e.g., at conferences, when interacting with professionals in the field)

      Patents and publications are expected to be the outcome of this project. There is a chance to present this work in professional conferences.

    • I expect students to work 8 hrs per week. I expect to meet with students 1-2 times each week for mentoring and discussion. Here is the type of activities that students will engage in each week.

      1. Receive training of any new experimental techniques
      2. Perform the basic material synthesis experiment for developing the solid electrolyte
      3. Characterize the solid electrolyte developed in our lab
      4. Analyze the characterization results
      5. Data analysis and/or failure analysis
      6. Monitor the battery testing and collect battery testing data
      7. Manage project progress and adjusting the design of experiments 

    • Hybrid

    • Dr. Beibei Jiang, bjiang1@kennesaw.edu

  • 2023-2024 First Year Scholars: Cassidy Moreau, David Roque, and Armani Williams

    • Currently there are two main radiation therapy procedures that are the most prevalent for cancer treatment. They are low-dose radiation (LDR) and high-dose radiation (HDR). Each has its pros and cons, such as risks to healthy tissue besides the targeted tumor area, or the duration of the therapy from 6 weeks to several months.

      Another issue is that patients may be in rural areas or locations that are far away from radiation therapy clinics. In some cases, the patients and family members need to acquire accommodation close to the clinics for a certain period of time until the treatment is complete.

      We are designing a novel implantable, wireless radiation capsule, that can be opened and closed remotely, to deliver or block radiation with several openings designed to deliver radiation dose only to the target tumor area with minimum to no radiation to surrounding healthy tissue.

      This technology can benefit cancer patients in 3 main ways:

      1. Help certain populations far away from radiation therapy clinics
      2. Minimize risk of radiation to healthy surrounding tissue
      3. Minimize total duration of treatment as well as setup time and precision for radiation dose delivery. 
      1. Learn to use software to design, calculate, and optimize designs for the capsule and implantable antenna.
      2. Learn to conduct a literature review and summarize and present findings of the  literature review.
      3. Learn to create PowerPoint or word documents to present research findings.
      4. Learn to write a draft of an IEEE publication for conferences
      5. Learn to work in research teams and communicate research findings. 
      1. Attend research meetings and provide updates using PowerPoint.
      2. Conduct literature review and update PowerPoint slides with research findings.
      3. Learn to use necessary software for the assigned task within the larger project. 

    • Hybrid

    • Dr. Hoseon Lee, hoseon.lee@kennesaw.edu

  • 2023-2024 First Year Scholars: Sam Amoah

    • Direction of Arrival (DoA) estimation using spatially separated antennas has a rich history in wireless communications; however, developing DoA methods specifically for Vehicle-to-Vehicle (V2V) networks has received little attention. Determining the DoA of an incoming safety message could allow V2V networks to provide better collision avoidance services to drivers amid positioning errors by correctly estimating other vehicles in relative azimuth.

      Multiple-channel receiver DoA methods are very accurate, but often exhibit high front-end complexity rendering them expensive for deployment. Single-channel receiver DoA methods can also require front-end complexity which could render data recovery in V2V networks difficult. In this project, we seek to develop a novel DoA method for a single-channel receiver which uses an unbiased four element partitioned antenna array and baseband processing using a correlation pattern map and/or potentially a matched filter bank. The system components will be derived and evaluated in simulation and fabricated and experimentally tested to reveal an accessible method for estimating the DoA in V2V networks which could also have applications in other wireless networks.

      Come Have Some FUN!

    • Students will:

      1. Work effectively as part of a team of 2 FYSP participants
      2. Define the terminology associated with research and theory in their field
      3. Describe past research studies in their field of study
      4. Locate primary and secondary sources related to their field of study
      5. Write a research paper
      6. Present their research/creative activity to an audience (e.g., poster, oral presentation, performance, display)
      7. Reflect on their research project, including strengths, weaknesses, and things they would do differently in another research context
      8. Students throughout the project will be challenged through problem-solving, persistence on tasks, and time management. This is both a hardware and software research project, with research platform fabrication and experimental work

    • Semester 1:
      Weeks 1-3: Orientation, lab policies, assigned bibtex training, assigned literature survey papers, Gantt chart formation.

      Semester 1:
      Weeks 4-6: Literature survey writing, assigned LaTeX training, training in MATLAB simulations.

      Semester 1:
      Weeks 7-16: Research work in algorithms and signal processing. Working on tasks in lab. Designing and fabricating antenna array.

      Semester 2:
      Weeks 1-3: Experimental design and troubleshooting.

      Semester 2:
      Weeks 4-6: Experimental data capture and analysis.

      Semester 2:
      Weeks 7-9: KSU Symposium of Student Scholar presentation prep, and publication drafting.

      Semester 2:
      Weeks 10-16: Publication drafting and submission.

    • Face-to-Face

    • Dr. Billy Kihei, bkihei@kennesaw.edu

  • 2023-2024 First Year Scholars: Amelia Dodson, Fernanda Herrera-Candanedo, and Jonathan Yeager

    • This project aims to use the following Research and Development Tools to achieve brain augmentation for the reinforcement of learning engineering concepts and content. Creating environments that can calculate how much reward will adequately motivate an operand is of great interest in engineering, and in this research exercise, 3D Immersive Environments, EEG sensing, monitoring, and processing Tools will be used. These Tools are all within the KSU-Vertically Integrated Program-Brain Augmented Technology Research Laboratory - (1) 14-Channel EMOTIV EPOC X Wireless Mobile EEG System; (2) 32 Channel EMOTIV Wireless EEG Brainwear® (3) Real & Virtual Visualization & Simulation Environment and Tools; and (4) Immersion 3D Content Development Tools (zSpace).

      The established relationships with Marietta Schools and Development assistance from Texas Instruments TI, for the Robotic System Learning Kit (TI-RSLK) and our EEG research Lab on Brain Augmented Technology studies, will play pivotal roles as we further develop pathways for the STEM-PASS Program. This effort is multi-disciplinary and comprises of the Electrical & Computer Engineering Department Students & Faculty, and the Marietta Schools' Teachers and students (especially Females & Underserved students). This effort will also provide a foundation for responses to RFPs from Agencies such as the National Science Foundation NSF, Naval research Office NRO and the Army Research Office ARO, in the foreseeable future.

    • At the end of each Program period, participants would have demonstrated the value of the following:

      1. Mentoring relationships and the role that gender plays in STEM mentoring, particularly cross-gender mentoring relationships and whether they encourage positive socialization to the field in the same manner as same-gender mentoring relationships.
      2. The role of gender in different types of mentoring models and in the terms of mentoring relationships (i.e., formal, or informal). For instance, studies could examine whether males and females in STEM fields receive the same benefits through formal and informal mentoring programs or whether mentoring relationships that utilize the citizen model facilitate the retention of females within STEM disciplines.
      3. The elements of successful mentoring relationships formed by females in STEM disciplines to provide a more holistic picture of what factors need to be included in the design of such mentoring programs for maximum benefits.

      Outcomes

      1. Learn and understand Electrical and Computer Engineering ECE concepts such as Voltage, Current, Power & Energy.
      2. Learn about and understand Component Design, Assembly and Testing.
      3. Learn and understand Micro-Controller interfaces with Sensors, Actuators & Motors.
      4. Learn and understand 3D Immersive Environments, EEG sensing, monitoring, and Data processing Tools/use.

    • Weekly Duties:

      1. Get in Group discussions about how to be a good Team Player
      2. Review the Literature on EEG Applications and Robotics System Engineering & Technology
      3. Assemble and operate TI-RSLK
      4. Guided CODE Development exercises
      5. Test a TI-RSLK
      6. Data study and Analysis
      7. Create Presentations on the Study
      8. Write Reports on the Study
      9. Participate in regular Group Meetings to build rapport and relationships
      10. Publish to present at STEM Conferences and KSU Annual Poster Sessions

    • Face-to-Face

    • Dr. Cyril Okhio, cokhio@kennesaw.edu
      Dr. Tim Martin, tmart125@kennesaw.edu 

  • 2023-2024 First Year Scholars: Celina Bartolo-Jacobo

    • Solar power has the potential to provide free energy in a clean and sustainable manner. One difficulty of extracting solar power occurs during shading caused by adjacent objects, clouds...etc. The project will develop a new technology for mitigating the negative impact of shading on solar power generation to increase the generated power.

      The technology relies on a camera for collecting images for a solar system which are utilized through image processing to extract important information for optimal operation of the solar system. The research outcome conducted in this program will be used for validating the technology and support its commercialization.

      • Define terminologies associated with solar energy research and theory in the power engineering field.
      • Describe past research studies in the area of partially shaded PV systems.
      • Articulate the contributions in the conducted research.
      • Synthesize and critically analyze past research in their field of study and identify the literature gap.
      • Collect data for training a neural network model.
      • Analyze, synthesize, organize, and interpret the experimental data.
      • Write one or two research papers.
      • Present their research/creative activity to an audience in a conference.
      • Understand the value of scientific research and the value of science and investigation.
      • Articulate the ways in which their research participation helps prepare them for graduate school and/or a career
      • Describe appropriate professional conduct and build proper communication skills.

    • • Research the operation and components of solar PV systems.
      • Research partial shading in PV systems and contemporary industrial standards of operation and protection.
      • Model and simulate electrical systems using computer software’s such as MATLAB/Simulink.
      • Write high quality weekly reports.
      • Conduct experiments and collect data.
      • Test experimental prototypes.
      • Use library to search for existing research relevant to their research.

    • Hybrid

    • Dr. Yousef Mahmoud, ymahmoud@kennesaw.edu

  • 2023-2024 First Year Scholars: David Beverly, Prince Jeewani, Kevin Kellner, and Peyton White

    • Solar panels are made of individual solar cells, which convert the sunlight into renewable electricity. Some solar cells develop defects at the time of their manufacturing. These defects are not visible by human eye or a normal camera. Defective solar cells can reduce the overall operating efficiency and may cause premature failure of solar panels. When assembling solar panels, rejecting defective poor-quality cells, and selecting high-quality solar cells are of high importance to ensure long-lasting solar panels are delivered to the customers. Hence, it is essential to develop robust inspection techniques to detect hidden sub-surface defects in solar cells for improved solar panel manufacturing.

      In this project, we aim to fabricate a low-cost instrumentation for solar cell inspection using multi-color scanning laser beams. Our method can quantitatively identify small sub-millimeter scale buried invisible structural defects in a solar cell. The proposed technique can also help in identifying various electrical parameters of a solar cell that play critical roles in its operation and power conversion efficiency. Such comprehensive testing mechanism will allow better quality control, as well as identifying routes to improve the manufacturing processes in the future.

      The specific aim of this project is to design and build a low-cost instrument and its control software to perform experiments under different temperatures, varying broadband light irradiation, different color pulsed and continuous-wave scanning laser beams, then acquire measurement data, and demonstrate its capability of identifying defects in solar cells quantitatively and graphically.

      The first-year research scholar will gain valuable knowledge on solar cell technology, receive hands-on training in optical and electronic measurements and testing of solar cells, learn to build circuits, instrumentation, and applied computer programming. In addition, the FYSP scholar will develop many other important engineering research skills, critical thinking skills, and communication skills through this project.

      1. Learn how to perform literature research and formulate creative solutions.
      2. Build functional electronic circuits.
      3. Learn solar cell test and measurement procedures.
      4. Program microcontrollers and test embedded systems.
      5. Learn how to operate various lab instruments.
      6. Apply 3D printing and assembly.
      7. Implement data plot and data analysis techniques.
      8. Develop teamwork and presentation skills.
      • Read research articles to learn about solar cell testing and measurement.
      • Design experiments and perform tests on solar cells.
      • Program microcontrollers and perform data acquisition.
      • Analyze experimental data and plot graphs.
      • Attend weekly research group meetings and update the Advisor.
      • Document experimental data and make presentations.

    • Students will be flexible to work in a hybrid format for this project. Many tasks such as literature research, data analysis, virtual meetings, presentations, report and manuscript writing can be accomplished remotely and do not require to be on campus, whereas some other important tasks such as performing hands-on experiments, data collection, debugging etc. needs to be performed in the lab.

    • Dr. Sandip Das, sdas2@kennesaw.edu 

  • 2023-2024 First Year Scholars: Tiger Wang

    • The project goal is to develop a light-based wearable sensor that can non-invasively and continuously assess the brain and muscle health in children with sickle cell disease (SCD). Sickle cell disease is a genetic disorder and annually ~300,000 new babies are born with SCD worldwide. Due to chronic anemia (impaired oxygen delivery) and abnormal perfusion, SCD has a profound effect on multiple organs including brain and muscle. Particularly, children with SCD have a 300 times higher risk of stroke compared to the general population.  It is also known that SCD induces skeletal muscle dysfunction affecting daily life physical activities in SCD patients. Thus, wearable sensor for continuous measurement of oxygen level of local tissues would be helpful to predict the risk of SCD-related symptoms and monitor the therapeutic effect. 

      The proposed wearable sensor utilizes an optical technique called near-infrared spectroscopy to measure the changes of tissue oxygenation. The near-infrared light can penetrate deep (~1cm) into a skin so that it can collect data on oxy- and deoxy-hemoglobin concentrations in brain/muscle tissues. The wearable sensor will consist of miniaturized LEDs and photodetectors, analog circuits and microcontroller, and Bluetooth module for wireless communication. The compact form factor of the sensor will allow for attachment on forehead and forearm muscle or thigh for data collection during activity. 

      In this project, undergraduate students will assist with design/build/verification of light-based medical devices. If the prototype is successfully built, validation test will be performed against the custom NIRS system, flexNIRS by researcher at Massachusetts General Hospital, and commercial system, PortaMon made by Artinis Medical System. Student can indirectly experience the entire cycle of medical device development. Also, “Biomedical optics” is an emerging field that studies the basic principles of interaction between light and biological tissues. Light as a medium for tissue sensing has a huge potential of clinical translation or wearable health monitoring like Apple Watch. 

      • Gain essential knowledge on biomedical optics and pathophysiology of sickle cell disease
      • Understand a principle of light-based sensors (Like Apple Watch)
      • Learn an electronic system to operate light sources and detectors
      • Gain experience in designing and building a compact electrical circuit board
      • Collect data using commercial NIRS system
      • Apply 3D printing to build a custom enclosure for wearable sensor
      • Perform optical spectroscopic sensing and data analysis
      • Implement Bluetooth module
      • Enhance professional communication skills
      • Literature study in biomedical optics
      • Prototype development (assist with circuit and PCB design) 
      • Perform the device tests
      • Run simulation on photon propagation in tissues
      • Data analysis on the acquired optical data
      • Present research progress in a weekly lab group meeting
      • Write an abstract and prepare presentations for conferences.  

    • Hybrid

    • Dr. Paul Lee, slee274@kennesaw.edu 

  • 2023-2024 First Year Scholars: Stephen Colletta, David Cruz, Nathan Hamilton, and Brianna Jenkins

    • Recently, neuromorphic hardware platforms like Loihi have demonstrated superior energy efficiency in solving certain convex and combinatorial optimization problems while achieving similar quality solutions as the solutions that can be obtained using conventional digital hardware (CPUs and GPUs). These results in conjunction with recent advances in quantum-inspired classical computing methods have opened the possibility of achieving neuromorphic supremacy where certain computational tasks are energetically more suitable for neuromorphic architectures. “What are those tasks, and how can we demonstrate neuromorphic supremacy?” is the primary goal of the proposed project. We will delve into the physics of optimization that governs the dynamics in neuromorphic systems and the participants will also explore synergies between different neurodynamical principles and formulations used in quantum-mechanical systems. We plan to explore how some of these quantum-inspired neuromorphic techniques can be mapped onto existing neuromorphic simulators/hardware and can be used for solving NP-hard problems. We will benchmark these approaches with the current state-of-the-art and articulate possible hardware improvements required to achieve neuromorphic supremacy goals. 

      In the proposed project, our first-year scholar will collaborate with other members of our research lab, and begin with understanding the combinatorial optimization problem and neuromorphic systems. More importantly, the scholar will explore the related neuromorphic computing algorithms that can smoothly operate on an edge computing device. 

      • Gain essential knowledge and skills in AI, machine learning, and embedded systems.
      • Learn skills related to the assembly and configuration of drones.
      • Understand the event camera and be able to design related algorithms.
      • Explore the algorithm design under the hardware constraints and tradeoffs.
      • Collaborate with undergraduate and graduate students in other teams.
      • Gain research skills systematically and understand the research process.
      • Acquire abilities in academic writing, presentation, and communication.
      • Improve skills in solving practical engineering problems.
      • Weekly meeting and report the progress.
      • Discuss the project with the advisor and collaborators.
      • Study algorithms and explore the implementation on hardware.
      • Evaluate the system performance.
      • Accomplish a final report or complete a research paper.
      • Participate in drafting external grant proposals.

    • Hybrid

    • Dr. Yan Fang, yfang9@kennesaw.edu 

  • 2023-2024 First Year Scholars: Thomas Brown, Solomon Fleury, and Christine Marie Lirazan

    • To enable NASA's science and exploration missions, the use of robots to perform space operations is always needed as stated by NASA’s Human Robotic Systems. This research proposes the design, fabrication and control of a drone robot to perform navigation in complex terrains.  The final design of this project is a prototype that is capable to operate in hostile environments, investigate candidate destinations and provide vital information to prepare for human explorers.  

      1. The student will learn how to work with a 3D Printer to design and fabricate different components for the robot.
      2. The student will learn how to work with a microcontroller/microprocessor to control different parts of robots and fly the robotic drone.
      3. The student will learn how to model a robot in a simulation environment and study its behavior and movement. 
      1. Attend weekly progress meetings.
      2. Read the materials assigned.
      3. Learn and practice with Matlab and Simulink to model robots.
      4. Learn and practice to work with a 3D Printer.
      5. Learn and work with microcontrollers/microprocessors such as Arduino and Raspberry PI. 

    • The student has the option to work hybrid.

    • Dr. Turaj Ashuri, tashuri@kennesaw.edu
      Dr. Amir Ali Amiri Moghadam,  aamirimo@kennesaw.edu  

  • 2023-2024 First Year Scholars: Isabel Acklen

    • The aging baby boomer blood donor base, coupled with decreases from younger age groups, is an ongoing public health concern and impacts all people in need of blood transfusions regardless of gender, age, racial, or ethnic background. There is an urgent need to expand the blood donor pool to include more younger generations, first-time donors, and minorities.

      The integration of virtual reality (VR) technology and mobile apps represents a cutting-edge innovation in the field of blood donation. Leveraging the immersive capabilities of VR, the project seeks to alleviate anxiety, discomfort, and fear experienced by donors, particularly first-time donors, during the blood donation process. In this project, we will investigate the cognitive load of donors, such as anxiety, stress, and sensory overload, through different survey instruments while using VR during blood donation. 

    • The student will:

      1. Describe past research studies in their field of study
      2. Evaluate research studies they see in the media or encounter in literature
      3. Write papers and research reports
      4. Develop problem-solving skills
      5. Present their research activity to an audience

    • 1. Find papers related to the problem
      2. Summarize papers
      3. Find gaps in the research
      4. Discuss research directions with faculty mentors
      5. Meet weekly with faculty mentors
      6. Write research papers 

    • Hybrid

    • Dr. Robert Keyser, rkeyser@kennesaw.edu 
      Dr. Lin Li, lli19@kennesaw.edu
      Dr. Joy Li, yli49@kennesaw.edu 
      Dr. Maria Valero, mvalero2@kennesaw.edu 

  • 2023-2024 First Year Scholars: Oreoluwa Dawodu, Aaron Grann, and William Thompson

    • In recent years, compliant mechanisms and flexible machines have garnered increasing interest from researchers, owing to their remarkable intrinsic properties, where their mobility arises primarily from the deformation of their members rather than traditional relative motion between neighboring links.

      As a member of our group, you will have the opportunity to work on diverse and impactful projects that align with your interests and aspirations. Here's a glimpse of the exciting research projects we offer:

      1. Navigation of a Fully Compliant Mudskipper using Reinforcement Learning: We developed a mudskipper robot which has already been accepted for presentation and publication at the prestigious ASME IMECE Conference in November 2023. Check out the robot's captivating video at https://youtu.be/kG1gmOw7ub0. The new focus will be creating trajectory patterns using reinforcement learning.
      2. Design and Development of a Compliant Knee Joint and Creating Walking Patterns using Reinforcement Learning: Join us in designing a novel compliant knee joint and explore the world of reinforcement learning to create walking patterns. Our initial designs have already been published at the 2023 IEEE SouthEast Conference, and we're excited to present them at the upcoming ASME IMECE Conference in November 2023.
      3. Design and Development of Novel Portable and Low-Cost Laboratory Equipment for Engineering Courses: Make a real impact by working on projects that directly benefit engineering education. Our team has successfully developed six laboratory equipment since 2020 and published five conference papers. Currently, we're focused on creating new lab equipment to demonstrate active and passive vibration control.
      4. MATLAB Simscape Models of Compliant Mechanisms and Flexible Machines: Interested in simulation and modeling? Attend our engaging weekly workshops to learn MATLAB Simscape, a powerful tool for exploring compliant mechanisms and flexible machines. Students who excel in the workshops during semester 1 will have the opportunity to continue with a research project in the following semester. Past research from this initiative has resulted in four conference papers and a journal publication, with students as first authors.

    • The supervisor, Dr. Ayse Tekes, has adopted a training model where students receive initial training from supervisors and experienced students to successfully carry out project tasks. Once trained, students will be responsible for training new students for designing complex CAD models of the new mechanisms in SolidWorks, 3D-printing using different filaments, selecting the suitable parts to be purchased that are affordable, building the experimental setup, conducting the experiment, acquiring data using the sensors, and simulating systems in MATLAB. 

    • Students will meet at least biweekly with the supervisor and experienced research team. Each project will start with conducting a thorough literature review, followed by working on previous designs, brainstorming new ideas, and modeling and prototyping the initial designs.

    • Face-to-Face

    • Dr. Ayse Tekes, atekes@kennesaw.edu

  • 2023-2024 First Year Scholars: Claire Brownyard, James Kyle, Hubert Love, Peter Samaan, and Adam Wille

    • Hydrogen based fuel cell technology is considered for the next generation of clean energy production. Fuel cells operate by reacting hydrogen (H2) and oxygen (O2) from air to generate electricity, producing H2O as the only byproduct. This project work will focus on conducting experimental research for the development of single button cells and performing electrochemical analysis.

      The First-Year Scholar will learn how to conduct basic research in fabrication and testing of these devices. A detailed literature survey will be conducted to identify processes and materials used in this system. The student will document the state-of-the-art electrode materials and potential research gaps will be identified. A detailed experimental procedure will be developed and discussed. The First-Year Scholar will learn various aspects of solid-state materials processing techniques and will learn the state-of-the-art methods to test these devices. Students will be involved in writing reports and publishing manuscripts. 

      1. Gain experience in solid-state energy technology.
      2. Conduct hands-on experimental research, generating results and performing data analysis for making meaningful conclusions.
      3. Learn the cutting-edge characterization techniques used in materials science.
      4. Engage in writing research articles and conference proceedings. 

    • The student will participate in weekly meetings with the research group to discuss the progress and plan for future experimental work. The student will conduct hands-on experiments in lab and analyze the generated data.

    • Face-to-Face

    • Dr. Ashish Aphale, aaphale@kennesaw.edu

  • 2023-2024 First Year Scholars: Nahtecia Housen

    • Elastography techniques are used to find wave speeds in bio-materials and with those wave speeds, we find the material/tissue/muscle stiffness. Muscle stiffnesses are important landmarks of muscle health.

      In this research project, we will use a novel method that will be a cost-effective way to find the wave speeds in various materials such as wood, plastics, bio-materials, etc. If this method is feasible we would then apply it to Achilles Tendon and biceps. We will find out if the velocity of shear wave propagation through the biceps brachii. Similar observations will be made when examining the Modulus of Elasticity of other materials such as plastics, wood, bio-materials etc. 

    • Students will be able to write a research article upon the results acquired in this study. They will also write an IRB proposal and become IRB certified.

      Measures and assessment of the outcomes will be made by:

      1- Development of experimental hardware setup
      2- Research Article with Professor
      3- Conference Paper submission

    • Weekly Duties are:

      • Setting up hardware for acquiring the data
      • Regular weekly interaction between the students and the advisor
      • Details/discussion for solutions to the research project
      • Conceptual design to satisfy research requirements
      • Design specifications necessary to purchase components, manufacture, and assemble the proof-of-concept prototype
      • Details of anticipated performance validation for the proof-of-concept prototype
      • Updated Research Plan with allocation of needed resources
      • Phase Review (including Oral Presentation and Written Report)

    • Face-to-Face

    • Dr. Muhammad Salman, msalman1@kennesaw.edu

  • 2023-2024 First Year Scholars: Joshua Daniel, Devon Hulse, and Arya Shah

    • A road debris is a substance, a material, or an object that is foreign to the normal roads. Road debris plays a crucial role in causing accidents on roads, especially on highways, considering the vehicle’s higher speeds.

      In this work, three pretrained convolutional neural network (CNN) models namely VGG16, MobileNetV2, and InceptionResNetV2 will be applied to classify five debris classes, namely barrels, car parts, puddles, salts, and trees. The dataset used in the models will consist of images of the above-mentioned debris which will be collected by taking thermal images using a thermal camera. The dataset will be divided into training, validation, and testing sets with each set consisting of 1000, 500, and 100 images respectively. The performance of the models will be observed for 10,20, and 30 epochs. The learning rate will be assigned to 0.0001 with Adam optimizer and a batch size of 10. At the end of trials, the training, validation and testing accuracy of all the three models will be measured. The confusion matrix will also be plotted for drawing conclusions.

    • 1. Understanding of Deep Learning Concepts: Students will gain a comprehensive understanding of the principles, architectures, and algorithms used in deep learning. They will learn about neural networks, activation functions, backpropagation, optimization techniques, and various types of deep learning models such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs).

      2. Programming and Implementation Skills: Through hands-on experience, students will develop programming skills in languages like Python and libraries such as TensorFlow or PyTorch. They will learn how to implement and train deep learning models, fine-tune hyperparameters, and troubleshoot common issues.

      3. Data Preparation and Preprocessing: Students will learn how to preprocess and clean data to make it suitable for deep learning tasks. They will gain insights into data augmentation, normalization, and other techniques to enhance the quality of the data.

      4. Problem-Solving Skills: Deep learning research involves addressing real-world problems and challenges. Students will develop problem-solving skills as they design experiments, make decisions on model architecture, and analyze results to draw meaningful conclusions.

      5. Critical Thinking and Research Methodology: Students will engage in literature reviews, analyze related works, and develop a critical perspective on the strengths and limitations of existing deep learning approaches. They will learn how to design research methodologies to answer specific research questions.

      6. Communication and Presentation Skills: Deep learning research often involves presenting findings and insights to peers and faculty members. Students will improve their communication skills through written reports, presentations, and discussions.

      7. Collaboration and Teamwork: Many deep learning research projects are collaborative efforts. Students will learn to work effectively in a team, delegate tasks, and combine their individual skills to achieve common research goals.

      8. Creativity and Innovation: Deep learning research encourages creativity and innovation. Students will have the opportunity to explore novel ideas, propose new architectures, or apply deep learning to unique domains.

      1. Literature Review: Spend time reading and reviewing relevant research papers, articles, and books related to the specific deep learning topic or problem being investigated.
      2. Data Preprocessing: If working with real-world data, students may spend time cleaning, preprocessing, and organizing the data to make it suitable for deep learning tasks.
      3. Model Implementation: Work on coding and implementing deep learning models using Python and deep learning libraries like TensorFlow or PyTorch.
      4. Model Training: Train and fine-tune deep learning models using the prepared data. Experiment with different hyperparameters and architectures to optimize model performance.
      5. Experiment Design: Collaborate with the research team to design experiments that address specific research questions or hypotheses.
      6. Testing and Validation: Conduct rigorous testing and validation of the trained models to ensure accuracy and generalization.
      7. Data Analysis: Analyze the results of the experiments and interpret the performance of the models.
      8. Troubleshooting: Identify and troubleshoot any issues or errors that arise during the model training or testing process.
      9. Meeting with Mentor: Attend regular meetings with the faculty mentor or research supervisor to discuss progress, receive feedback, and seek guidance.
      10. Collaboration: Engage in collaborative discussions with other team members, sharing insights and ideas to foster a supportive research environment.
      11. Documenting Progress: Maintain detailed documentation of the work done each week, including code, experimental setups, results, and any challenges faced.

    • Hybrid

    • Dr. Sathish Kumar Gurupatham, sgurupat@kennesaw.edu

  • 2023-2024 First Year Scholars: Christian Sargent

    • Traditionally, robots and wearable devices have mainly used electric motors and hydraulic/pneumatic systems. Unfortunately, these traditional methods have significant problems like being heavy, inflexible, and noisy. They can't match the impressive power efficiency of human muscles due to their bulky and cumbersome components. A new era is dawning for robotics and wearables, demanding advanced actuators that are super flexible, can move widely, and are as light as natural muscles.

      This drive for innovation has put the spotlight on artificial muscles, captivating the interest of pioneering researchers. One such innovation is the twisted and coiled actuator (TCA), a unique type of artificial muscle made from fishing lines or sewing threads. The TCA comes to life through a complex process involving twisting polymer fibers, and changes in temperature activate its movement. When it contracts, the TCA can achieve an impressive power output of 5.3 kW/kg, surpassing human muscle performance by an incredible factor of 100.

      TCAs come with many benefits, including their ability to deform significantly, their flexibility, lightweight design, quiet operation, and affordability. However, their weakness lies in how they handle temperature changes during their operation. This affects their dynamic performance. To make TCAs practical and widely usable, it's crucial to improve how they respond to temperature changes, especially rapid ones.

      Currently, our research focus is on using remarkable materials called carbon nanomaterials, specifically graphene and carbon nanotubes (CNTs), to enhance and speed up the way TCAs react. These carbon materials have excellent heat-carrying abilities, as numerous studies have confirmed. By incorporating graphene and CNTs, we aim to reduce the resistance that heat encounters within TCAs, making them more efficient at releasing heat during the cooling process. This partnership also takes advantage of their characteristics of low heat storage and quick heat movement, which can further accelerate cooling in TCAs.

      Introducing these carbon nanomaterials into the development of TCAs holds the promise of creating a significant transformation. This transformation would lead to quicker cooling, which, in turn, would greatly enhance the dynamic response of TCAs.

    • Students will be asked to work together to fabricate artificial muscles by coiling fish lines. They will be asked to learn how to measure the dynamic response of the developed artificial muscles using different equipment such as lock-in amplifier. They will be asked to measure thermal and mechanical properties of the developed artificial muscles. In addition, they will write a scientific report such as conference papers and journal papers. The students will also be asked to disseminate their research findings in academic conferences.

    • Students will be asked to attend weekly research meetings. Although the selected students will work independently, they will be asked to work with other undergraduate researchers in the lab. The students will have a chance to receive feedback from the faculty mentor and fellow undergraduate researchers frequently.

    • Face-to-Face

    • Dr. Jungkyu Park, jpark186@kennesaw.edu

  • 2023-2024 First Year Scholars: Andrew Marion, Elizabeth Owens, Lily Richard, and Madison Sanford

    • A Computational Fluid Dynamics (CFD) investigation delving into the intricate phenomenon of vortex breakdown over a compound delta wing at high angles of attack represents a crucial step in understanding the aerodynamics of complex aircraft configurations. This study focuses on comprehending the intricate interplay between vortices, airflow separation, and the resulting aerodynamic performance.

      A compound delta wing is a geometrically intricate configuration featuring multiple delta-shaped wings, often staggered or overlapped. At high angles of attack, this configuration is known to exhibit vortex breakdown – a phenomenon where the coherent vortex structures near the wingtips degrade into turbulent patterns, significantly affecting the aerodynamic forces and stability.

      Using CFD, a technique that numerically solves the governing Navier-Stokes equations, researchers can simulate and visualize the airflow over this complex geometry. The investigation begins by creating a virtual model of the compound delta wing, complete with details of wing surfaces, control surfaces, and the fuselage. The computational mesh, fine-tuned for accuracy, discretizes the flow domain to enable numerical solution.

      At high angles of attack, the airflow encounters adverse pressure gradients, causing flow separation. The presence of multiple delta wings intensifies this phenomenon, leading to the formation of strong vortices at the wingtips. As the angle of attack increases, these vortices may suffer a breakdown – a shift from organized structures to turbulent, chaotic flow patterns. This breakdown significantly alters the lift and drag characteristics of the wing, impacting its overall performance.

      The CFD simulation captures these intricate dynamics by solving the Navier-Stokes equations iteratively, simulating the behavior of air particles and vortices over a range of angles of attack. Advanced turbulence models, such as Reynolds-Averaged Navier-Stokes (RANS) or Large Eddy Simulation (LES), are employed to capture the transition from laminar to turbulent flow, vital for accurate vortex breakdown predictions.

      Post-processing of simulation results provides insightful visualization of flow patterns, pressure distribution, and vortex dynamics. This aids in identifying critical angles of attack where vortex breakdown initiates and how it evolves with increasing angle of attack. The data obtained from these simulations offers a comprehensive understanding of the aerodynamic behavior of the compound delta wing, aiding in optimizing its design for enhanced performance and stability.

      In summary, a CFD investigation targeting vortex breakdown over a compound delta wing at high angles of attack unveils the intricate flow physics inherent to complex aerodynamic configurations. This study bridges theoretical understanding with practical design considerations, providing aerospace engineers with valuable insights into optimizing performance, stability, and control mechanisms for next-generation aircraft. As aviation continues to explore unconventional configurations, such studies remain pivotal in shaping the future of aerodynamics and aeronautics.

    • Engaging in the investigation of vortex breakdown over a compound delta wing at high angles of attack yields a range of transformative student outcomes, spanning personal, academic, and professional domains.

      From a personal perspective, students involved in this research project experience substantial growth in critical thinking and problem-solving abilities. As they navigate the complexities of Computational Fluid Dynamics (CFD) simulations, turbulence modeling, and data analysis, they develop the capacity to dissect intricate challenges, formulate hypotheses, and design methodical approaches to address them. This hones their analytical skills and nurtures a mindset that embraces ambiguity and complexity.

      Furthermore, participation in this research nurtures a sense of curiosity and intellectual curiosity among students. They become attuned to the beauty of discovery and the thrill of uncovering insights that contribute to the broader realm of aerospace engineering. This newfound appreciation for exploration fosters lifelong learning, encouraging students to remain curious and engaged with evolving scientific and technological landscapes.

      Academically, students gain a comprehensive understanding of aerodynamics and fluid dynamics. The project exposes them to advanced concepts in vortex dynamics, airflow separation, and turbulence – domains that extend beyond standard classroom curricula. This enriched knowledge base not only elevates their academic standing but equips them with a holistic perspective that extends beyond theory into practical applications.

      In terms of professional development, involvement in this research cultivates skills that are highly transferable and desirable in various industries. Mastery of CFD tools and methodologies bolsters their proficiency in numerical simulations, a skillset applicable across engineering and scientific disciplines. Additionally, the experience of working in a collaborative, mentored environment refines their communication, teamwork, and project management proficiencies – attributes that resonate well in any professional setting.

      Perhaps most significantly, participating in this research empowers students to make a tangible contribution to the field of aerospace engineering. As they unveil the mysteries of vortex breakdown and its implications on compound delta wing performance, they add to the collective body of knowledge that shapes aviation's trajectory. This sense of contribution instills confidence and a profound sense of accomplishment, motivating them to continue seeking opportunities to innovate and push boundaries in their chosen careers.

      In conclusion, the investigation of vortex breakdown over a compound delta wing at high angles of attack leads to transformative student outcomes across personal, academic, and professional dimensions. As students cultivate critical thinking, expand their knowledge, and develop practical skills, they emerge not only as proficient engineers but also as curious, adaptive, and impactful contributors to the broader world of scientific exploration and technological advancement.

    • Throughout their involvement in the vortex breakdown research project focused on a compound delta wing at high angles of attack, students undertake a well-structured set of weekly duties that enable them to contribute effectively to the investigation while honing their skills and knowledge.

      During the initial phase, students engage in comprehensive literature reviews to establish a foundational understanding of vortex dynamics, aerodynamics, and relevant simulation techniques. This equips them with the background knowledge necessary to comprehend the research's objectives and significance.

      Subsequently, students work closely with mentors to formulate research questions and hypotheses. They participate in regular brainstorming sessions, where they contribute ideas and perspectives, fostering a collaborative environment that encourages creative thinking.

      As the investigation progresses, students allocate a portion of their weekly duties to conducting Computational Fluid Dynamics (CFD) simulations. This involves preparing the virtual model of the compound delta wing, setting up the computational mesh, and configuring the simulation parameters. Running simulations requires careful attention to detail and a grasp of numerical methods, allowing students to develop hands-on expertise in utilizing advanced software tools.

      A significant portion of their time is dedicated to post-processing and analyzing simulation results. This task involves visualizing flow patterns, pressure distributions, and vortex behaviors. Students interpret these findings to discern patterns, trends, and potential vortex breakdown occurrences at varying angles of attack.

      Weekly meetings with mentors provide a platform for students to discuss their progress, address challenges, and seek guidance. These interactions foster mentorship relationships, offering opportunities for in-depth discussions that enhance students' comprehension of the research's complexities.

      Additionally, students allocate time for collaborative discussions with peers involved in the project. These discussions promote knowledge sharing, allowing students to learn from each other's insights, strategies, and experiences.

      Furthermore, students engage in journaling or documentation of their weekly progress. This practice helps them track their growth, reflect on challenges, and refine their strategies for subsequent tasks.

      Lastly, students may be involved in outreach efforts to share their project's significance with the academic and broader communities. This could involve preparing presentations, posters, or even participating in seminars or conferences to disseminate their findings.

      In conclusion, students' weekly duties within the vortex breakdown research project entail a diverse range of tasks, from literature reviews to simulations, analysis, meetings, and collaboration. These responsibilities provide a structured framework for their active participation in the investigation, nurturing their skills, knowledge, and overall contribution to advancing the understanding of aerodynamics and vortex dynamics.

    • Hybrid

    • Dr. Gaurav Sharma, gsharma3@kennesaw.edu

  • 2023-2024 First Year Scholars: Brandon Kim and Kevyn Locke

    • The precise observation of animal behavior in high resolution presents a complex challenge, as it necessitates the continuous monitoring of a subject animal within the camera's field of view while allowing for unrestrained movement. One strategy employed to address this challenge is known as 'Lock-on-tracking,' wherein the entirety of the behavioral enclosure is adjusted to maintain the target animal's position. This concept has been effectively applied to diminutive animals such as small insects. During the locomotion of the target insect on a sphere, a motorized system orchestrates its rotation to reposition the target creature accurately. Notably, this apparatus has found utility across a spectrum of walking insect species.

      In previous work, we introduced the concept of the autonomous treadmill for a walking insect (Transparent Omnidirectional Locomotion Compensator (TOLC)) and successfully implemented the system. In this project, our objective aim to design and develop a portable insect treadmill for a fruit fly (Drosophila Melanogaster), integrating with a stereomicroscope dedicated to neural imaging. The key tasks of this project involve: (1) design the locomotion compensator (autonomous treadmill) to align with the current TOLC system, with a focus on integration with the commercial stereomicroscope (Leica M205) optimized for fluorescent imaging, thereby enabling the visualization of neural activities within the fruit fly; subsequently, (2) develop a control scheme the newly devised apparatus, ensuring precise animal tracking; and finally, (3) harnessing the capabilities of the stereomicroscope to capture and elucidate neural activities through imaging procedures, thereby exemplifying the practicality of the devised system.

      The successful realization of this project is poised to yield an innovative locomotion compensator completely interfaced with microscopic imaging technology. Participating students are expected to gain hands-on experience in engineering system development, featuring autonomous control mechanisms for randomly moving insects. Moreover, students will be exposed to engineering system design using an advanced 3D modeling program. Ultimately, participating students will obtain comprehensive insights into the realm of autonomous motorized systems and optical imaging, specifically tailored for the observation of neural activities. This project is expected to be conducted by undergraduate students in various encompassing diverse backgrounds fields such as engineering, biology, and computer engineering.

    • By the conclusion of the project, students will have achieved the following objectives:

      • Articulate the functioning model of a servo motor and proficiently manipulate its control mechanisms.
      • Explain and contextualize prior research endeavors related to the locomotion compensator.
      • Conceive and develop a locomotion compensator through the utilization of a 3D modeling tool.
      • Employ a computational program to meticulously analyze, synthesize, structure, and derive meaning from gathered data.
      • Compose a scholarly research paper or article based on the comprehensive study's findings.
      • Demonstrate their research or creative endeavor to an audience through mediums such as poster displays, oral presentations, performances, or exhibits.
      • Evaluate their research undertaking, appraising strengths and weaknesses, and identifying potential enhancements for future research scenarios.

      Furthermore, students will foster advancement in the subsequent facets: effective time management, enhanced self-confidence and self-esteem, cultivation of independent thought, adeptness in problem-solving, and refinement of organizational proficiencies.

      • Design/Fabricate a motion compensator, subsequently subjecting the system to rigorous testing.
      • Conduct a comprehensive survey of relevant literature and critically review pertinent research articles.
      • Determine the key kinematic parameters intrinsic to the motion compensator's operation.
      • Execute experiments, meticulously analyze acquired data, and draw meaningful conclusions.
      • Compose comprehensive reports detailing experimental processes and outcomes, followed by the presentation of the resultant findings.
      • Engage actively in a regular group or individual meetings conducted on a weekly basis.

    • Face-to-Face (although meetings with PI may take place via TEAMS)

    • Dr. Dal Hyung Kim, dkim97@kennesaw.edu

  • 2023-2024 First Year Scholars: Jordan Bailey, Charles Goode, and Luke Hammond

    • Many casualties and life-threatening accidents involving bicyclers occur at nighttime when visibility is poor. The lack of adequate and reliable lighting poses a major threat to the bicyclists at night as it becomes difficult for other vehicle drivers to see the slow-moving manual pedal bicyclists clearly at night. In case of hit-and-run incidents, often the injured bicyclist becomes physically impaired and is unable to quickly contact emergency services for medical attention, which may potentially make the difference between life and death.

      In this collaborative project with the Electrical and Computer Engineering (ECE) department, we aim to design and fabricate a self-powered smart safety helmet for bicyclists which could potentially reduce accidents and save lives. Our novel helmet will integrate solar cells and a micro wind turbine to power bright blinking LED lights integrated on the back side of the helmet, thus increasing nighttime visibility and safety. In addition, the helmet will have an integrated microcontroller, accelerometer sensor, and Bluetooth communication capability. By analyzing the accelerometer data in real time, our smart helmet will be able to detect if a biker falls or gets involved in an accident and can automatically send an emergency message to 911 (and/or) to the biker’s registered emergency contact through his Bluetooth paired phone. Our core technology developed in this project can also be tuned later to produce smart helmet versions designed for motorized bikers.

      This project is expected to improve road safety, bicyclers’ safety, and has a high potential for developing a patented product for commercialization in the near future. Fabrication of the helmet shell will be handled through 3D printing to allow adequate placement of the hardware including solar cells, micro turbine, battery storage and microcontroller. The project will allow students to gain experience in computer aided design as well as simulation of wind flow through specially design ports within the helmet. These ports will serve to channel airflow past the micro turbines resulting in power generation that is proportional to the cyclist speed. 

      1. Learn how to use solar cells for energy harvesting and storing in a battery. 
      2. Learn how to design and build electronic circuits. 
      3. Program microcontrollers and test embedded systems. 
      4. Create computer aided drawings and models.
      5. Apply 3D printing technique for prototype fabrication. 
      6. Perform experiments, acquire data, and do data analysis. 
      7. Develop teamwork and presentation skills.
      8. Create and present a research poster.
      9. Produce a summary report.
      • Perform literature research as directed.
      • Design and build circuits.
      • Program microcontroller and test the system.
      • Create computer aided models
      • Perform basic flow simulations
      • Document experimental data and prepare presentations.
      • Attend research group meetings and report the research progress to the faculty mentors. 

    • Hybrid

    • Dr. Valmiki Sooklal, vsooklal@kennesaw.edu
      Dr. Sandip Das, Sandip Das,  sdas2@kennesaw.edu 

  • 2023-2024 First Year Scholars: Preston Brantley

    • The emerging field of Artificial Intelligence (AI) is increasingly interfacing with human lives, prompting a need to make these interactions more intuitive, effective, and seamless. Notably, General Knowledge AI – a fusion of technologies such as Natural Language Processing, Interpretation, and Speech Recognition – holds significant promise in advancing human-AI interaction. However, to leverage the full potential of AI, there's an essential need to enhance its existing capabilities, especially in real-world robotics control and communication.

      The research project titled "Advancing Human-AI Interaction: Enhancing General Knowledge AI for Real-World Robotics Control and Communication" is envisaged in this context. It strives to elevate the cognitive abilities of AI, focusing on understanding, reasoning, learning, and problem-solving to create a more responsive AI system capable of comprehending and acting upon complex instructions.

      The project leans heavily on the significant strides made in generative pre-training AI. These systems have shown remarkable language comprehension and response generation proficiency, acting as a robust foundation for our research. By building upon this groundwork, we aim to adapt and enhance these models to create an AI capable of human-like interaction and advanced robotic control.

      Our primary objective is to develop an AI system that enables users to instruct and control robotic systems using their voice, improving user convenience and accessibility significantly. In addition, we will explore how enhanced AI can facilitate more effective human-robot communication, focusing on understanding and acting upon the intricacies of human language and behavior.

      The research extends beyond mere theoretical advancements and strongly emphasizes practical implementation. We plan to integrate our enhancements with existing robotic systems and communication platforms, ensuring real-world usability and immediate benefits.

      The convergence of AI and robotics, as envisioned in this project, promises a new epoch of human-technology interaction. By enhancing the General Knowledge AI capabilities, we intend to create a future where humans and machines can communicate and collaborate effectively, fostering a symbiotic relationship. The eventual goal is a harmonious coexistence where technology intuitively understands and caters to human needs.

    • Engaging in this research project will yield multifaceted outcomes for participating undergraduate students, enriching their academic and professional profiles significantly. These outcomes align with crucial areas of development for early-stage scholars, focusing on technical and non-technical competencies.

      Firstly, students will be submerged in an environment that stimulates creativity and innovation. As they grapple with the challenges of enhancing pre-trained AI models, they are encouraged to think beyond the existing trend and introduce novel ideas. This experience enriches their academic portfolio and nurtures an inventive mindset that is invaluable in their future endeavors.

      Secondly, the hands-on aspect of the project heavily involves software development and hardware understanding. This will enable students to navigate and understand AI software models and physical robotics systems, cultivating critical skills in these increasingly prevalent fields. This robust knowledge base will substantially enhance their marketability, equipping them with highly sought-after skills in the job market.

      In addition, students can improve their research capabilities, from conducting literature reviews to synthesizing findings, thereby refining their ability to navigate the research landscape. They will also gain proficiency in technical writing, an essential skill in communicating complex ideas clearly and concisely, further amplifying their research competency.

      Finally, this project also emphasizes non-technical skill development. Through team-based activities, students will hone their communication and collaboration skills, which are critical for any career. Through mentor-guided teamwork, students will also understand the importance of mutual respect, cooperation, and diversity in accomplishing shared goals.

    • Each week, students will participate in structured activities designed to facilitate their progress and improve their research skills. The week will begin with a team meeting, where each student will provide updates on their progress, discuss any challenges they faced, and outline their goals for the upcoming week. This collaborative environment will foster peer-to-peer support and ensure efficient communication across the team.

      To ensure students fully comprehend and articulate their research, they must present their findings and review related literature papers at least twice per semester. These presentations will provide them with valuable experience in academic communication, improve their understanding of the research process, and deepen their knowledge of the project's broader context.

      Students will also maintain a weekly log detailing their activities, progress, challenges, and insights. This exercise will reinforce their technical writing skills, promote reflective learning, and provide a valuable record of their research journey.

      Finally, their weekly activities will include a comprehensive literature review, reimplementation of existing models, software development, hardware testing, and brainstorming sessions. This multifaceted approach will immerse students in the project, providing them with a holistic understanding of AI and robotics research and enabling them to make meaningful contributions to the project's success.

    • Hybrid

    • Dr. Razvan Cristian Voicu, rvoicu@kennesaw.edu

  • 2023-2024 First Year Scholars: Jacob Riad

    • We will develop a master/slave system using a twin Stewart mechanism as a special joystick with 6 DOF. This design is advantageous because the robot’s motion would be very intuitive, and the surgeon can control the robot end-effector just by one hand. Consequently, as the surgeon moves or rotates the joystick in any given position or orientation the robot follows that accordingly.    

      Design objectives: The joystick must have 6 DOF, be fully controlled with one hand, and be intuitive to use. Also, for convenience the workspace of the joystick must be a small volume within the range of surgeon’s hand motion.

      Design process: The overview of design process, and the components of the user interface system are demonstrated in Fig 3b, and Fig 11 respectively. A Stewart mechanism is chosen as a joystick since it has 6 DOF, and acks as a master system for the soft robot. The kinematics of the Stewart mechanism will be used to obtain its size based on the required workspace. Next, the structure of the mechanism can be 3D printed and assembled. Linear potentiometers will be mounted on each leg of the Stewart mechanism so that it can sense its displacement. This will translate the surgeon’s hand motion to its equivalent motion in the passive legs that must be mapped to required bending motions in the active links of the soft robot. This will be done through calibration and nonlinear mapping based on the bending profile of the soft robots’ legs. Finally, this data will be used as a desired input motion of the soft robot. The position of the robot will be sensed by an EM tracker attached to the robot end-effector which will be mapped to the equivalent bending deformation of the robot legs through the kinematics model and feedback to the controller.

      1. Performing literature review on research topics using google scholar
      2. Design of robot parts using Solidworks
      3. Understanding the Kinematics of robotic systems
      4. 3D printing of robot parts
      5. Writing research reports
      6. Data acquisition using microcontroller
      7. Programing a microcontroller to control electromotors
      1. Design CAD models of the robot
      2. 3D printing the required part
      3. Assembling the robot parts
      4. Writing weekly progress reports
      5. Be a team player and work with the graduate students for the project success.

    • Face-to-Face

    • Dr. Amir Ali Amiri Moghadam, aamirimo@kennesaw.edu 

  • 2023-2024 First Year Scholars: Arielle Charles, Aiden Kovarovics, Andrea Martinez Angulo, Shrey Patel, and Jonathan Ridley

    • This research project centers around collaboration with quadruped robots like the Boston Dynamics Spot Dog. Our objective is to reverse engineer the computational and mechanical aspects of the robot, aiming to enhance its capabilities for broader applications. We intend to integrate obstacle avoidance and path planning algorithms into the robot dog and collect data on navigation efficiency. We will enhance our research by introducing diverse robot systems, such as drones and on-ground robots, to work synchronously in a collaborative environment.  

    • Robotics Engineering: Students will gain hands-on experience in disassembling, reassembling, analyzing, and reverse engineering the robot's mechanical and computational components, deepening their understanding. 

      Algorithm Development: Participants will master creating and optimizing obstacle avoidance and path planning algorithms, adapting them for real-time decision-making in dynamic environments.  

      Programming and Integration: Proficiency in programming languages like Python and C++, capable of autonomous navigation and collaboration. Development with ROS and Motion Capture software.  

      Data Collection and Analysis: Real-world experiments will teach students how to collect, process, and analyze data, evaluate algorithm performance, and identify areas for improvement.  

      Problem-Solving and Innovation: Students will develop strong problem-solving skills as they tackle challenges in reverse engineering, algorithm development, and collaborative robotics, fostering innovative thinking.  

      Project Management: Participating in this research project will enable students to develop a wide range of skills, including time management, self-confidence/self-esteem, independent thinking, problem solving, organizational skills, leadership skills, intrinsic motivation, and persistence in tasks. 

      1. Independent Studies and literature review on topics: inverse kinematics applications, microcontrollers, multi-robot applications, motion capture, and obstacle avoidance algorithms.
      2. Attend group meetings, gather and analyze data, and discuss what action to take for the upcoming week.
      3. Understand the robot schematics and algorithms, and create algorithms based on the components needed for the robot.
      4. Take a video or write a report for each participating member in this research weekly, including what students did during the week. The video must include students' work during the week if students choose to record a video.  

    • Face-to-Face

    • Dr. Muhammad Hassan Tanveer, mtanveer@kennesaw.edu 
      Dr. Razvan Chris Voicu, rvoicu@kennesaw.edu 
      Dr. Nazmus Saqib, nsakib1@kennesaw.edu 

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