REU 2025 Summer Projects
List of Summer Projects
- Augmented Reality Development for Propulsion Systems
- Cybersecurity Policy Enforcement on Aerospace Systems
- Automatic Control of a Liquid Fuel Desulfurization System
- Collision Avoidance Between Low-Altitude Aircraft and Birds using Artificial Intelligence to Improve Airspace Safety
- Inclusive Robotic Navigation based on Robot Dog
- Thumbs up or down? Harnessing Social Media, AI, and Statistics to Drive Public Acceptance of Autonomous Systems
- Robotic Orthosis to Maintain Astronaut Strength in Space
- Optimal control for bio-inspired swimmers
- Autonomous Control of High Drag Surfaces for Distributed Atmospheric Sensing
- Navigation of Microgravity Surfaces Using Tethers
- Additive Manufacturing for Repair and Maintenance of Autonomous Systems
- Additive Manufacturing to Reduce Autonomous Systems Weight
Summer Project Descriptions
Augmented Reality Development for Propulsion Systems
We are offering an exciting summer research opportunity for a motivated student to work on developing augmented reality (AR) simulations that enhance the engineering and operational understanding of propulsion systems. The selected student will collaborate with a multidisciplinary team to design and create interactive AR applications that visualize propulsion components and assembly workflows in a virtual environment.
This project will involve integrating real-world data and operational guidelines into user-friendly AR interfaces to support training and troubleshooting in engineering contexts. Ideal candidates should have an interest in AR technology, a basic understanding of propulsion or mechanical systems, and a passion for exploring innovative solutions in engineering. This opportunity is perfect for students eager to apply AR to practical engineering challenges and gain hands-on experience at the cutting edge of system visualization and support.
Cybersecurity Policy Enforcement on Aerospace Systems
Engineered systems 鈥 including autonomous aerospace systems (e.g., uncrewed aerial systems or drones), robotics, and many more 鈥 rely on different digital technologies (e.g., computing, communication, data storage) during the system鈥檚 design, project management, and operational phases. Due to the use of digital technologies and environment in the engineered system鈥檚 lifecycle, potential cybersecurity attack surfaces expand their impact on system reliability, availability, and its operational information. The need to mitigate the impact of a potential cyber breach is now a contending constraint in the engineered system design lifecycle, as defined and analyzed in cyber-informed engineering (CIE) principles.
To that end, the project will follow the NIST Cybersecurity Framework to map digital assets, determine attack surfaces, and implement cybersecurity policy enforcement throughout the lifecycle of an engineered system. The deliverable of the project will be a documentation of policy statements as well as implementation guidance for specific policy enforcement points in the system. A testing method for validation as well as metric evaluations for continuous cyber resilience will also be part of the deliverables. Engineered systems for case studies will be determined with the advisor.
Automatic Control of a Liquid Fuel Desulfurization System
Sulfur in liquid fuels causes numerous serious problems, including poisoning fuel cells, corroding equipment, and emitting harmful pollutants. The sulfur content in JP-8 and diesel, for example, could be as high as 3000 ppmw (part per million by weight). Combustion of sulfur content fuels releases sulfur dioxide that is one of the main causes of acid rain. Fuel storage tanks, pipelines, and refining equipment suffer extremely high equipment maintenance cost because of sulfur corrosion.
The U.S. Army is not able to use logistic (sulfur contained) JP-8 fuel for fuel cell power due to sulfur poisoning fuel cell materials. The Environment Protection Agency (EPA) requires sulfur content in the ultra-low sulfur diesel (ULSD) to be 15 ppmw or less while fuel cell prefers the sulfur content 1 ppmw or less. Clearly, effectively removing sulfur from liquid fuels is imperative. The Objectives of this REU project is to improve the benchtop semi-auto controls into automatic controls for a desulfurization system. The controls of the system include temperature, pressure and flow rate. Outcomes from this REU project will strengthen our research in the desulfurization field.
Collision Avoidance Between Low-Altitude Aircraft and Birds using Artificial Intelligence to Improve Airspace Safety
Various types of Advanced Air Mobility aircraft 鈥 such as drones or uncrewed aerial vehicles (UAVs) and electric vertical takeoff and landing aircraft (eVTOLs) 鈥 are being planned to soon start transporting packages, cargo, and people over short-distance routes, especially across congested urban areas. These aircraft will fly at the lower altitudes (below 400m) of the National Airspace System (NAS), where they will share the airspace with birds. The risk probability of bird strikes with these aircraft is highest at these low altitudes. Figure 1 illustrates the potential risk of collisions between UAVs and birds.
To address this airspace safety challenge, the goal of this project is to develop advanced AI models to (1) identify species of bird based on sensor data (e.g., images, videos) and (2) model and predict movement of a flock of birds based on historical bird movement data. The bird movement predictions will then be used to plan safe flight trajectories for UAVs and eVTOLs to mitigate the risk probability of birds strikes during their flights in the NAS.
Inclusive Robotic Navigation based on Robot Dog
Robotic navigation aids humans in essential scenarios, including airport customer boarding, commercial meeting receptions, and disaster site navigation. While individuals benefit from robotic services, these services pose accessibility challenges for people with disabilities. As robotic services become increasingly prevalent, ensuring they are inclusive and accessible is crucial, accommodating human disabilities with adaptations such as slower movements, standing support, and hazard detection.
To address this issue, this study introduces a novel Accessibility-Aware Reinforcement Learning model (ARL) to observe human behaviors and adjusts robot motions to provide inclusive assistance to individuals with disabilities.
Thumbs up or down? Harnessing Social Media, AI, and Statistics to Drive Public Acceptance of Autonomous Systems
Whether new technologies and autonomous systems (e.g., drones and air taxis) see the light of the day or not, whether they take off or not, and whether they go from the lab to the market or not largely depends on their public acceptance, which, in turn, governs the certification and policymaking surrounding these systems. Hence, there is a strong need to carry out system 鈥渄esign for public acceptance鈥, with an emphasis on system characteristics (e.g., safety and privacy) that drive public acceptance, while optimizing for performance and cost.
The goal of this research project is to address this research need by mining publicly available social media data (e.g., Reddit, Quora, and Twitter/X posts, comments, questions, and replies) on autonomous advanced air mobility aircraft (e.g., drones and air taxis), performing sentiment analysis on data using AI/ML and conducting statistical analysis of the data. Research findings are expected to inform the development of a mathematical model on public acceptance for the design of future engineered systems and generate insights on strategies to improve public acceptance for existing systems struggling to gain widespread public support and adoption and regulatory approvals. These findings would allow the government and industry to reshape the national strategies around autonomous systems and guide future research to better address the key public concerns curbing public acceptance of such systems.
Robotic Orthosis to Maintain Astronaut Strength in Space
Astronaut exposure to the microgravity environment of spaceflight results in a loss of muscle mass and a decline in muscle strength and physical endurance. Astronauts need about two-hours of exercise each day to alleviate this loss of muscle mass. Existing remediation systems, such as whole-body exoskeleton, are too bulky and complicated.
This project is dedicated to developing a compact, universal and reconfigurable wearable robotic orthosis that can be used for any joint for astronauts depending on their individual health needs. The figure shows the orthosis is expected for the assistance and countermeasures in shoulder joints.
Optimal control for bio-inspired swimmers
Identifying optimal swimming gaits (kinematics) is essential for designing high-performance bio-inspired swimming robots. However, this task is challenging due to the high-dimensional parameter spaces involved, as it requires managing numerous control parameters. Traditional optimization approaches face scalability issues because the number of function evaluations (flow simulations) grows proportionally with the number of control parameters. For instance, with 1 million control parameters, 1 million flow field simulations would be required鈥攅ach taking several days to complete鈥攎aking such methods impractical.
To overcome this limitation, we have developed an adjoint-based optimization algorithm that significantly reduces computational cost. Unlike conventional methods, this approach requires only two flow field simulations to compute the gradient, regardless of the number of control parameters. The objective of this project is to adapt and apply this adjoint-based optimization algorithm to bio-inspired swimmers, enabling the identification of their optimal swimming gaits efficiently.
Autonomous Control of High Drag Surfaces for Distributed Atmospheric Sensing
The continued miniaturization of sensors, microprocessors, and transceivers is enabling massively distributed sensing of atmospheric conditions, at scales and resolutions that are not achievable by conventional weather balloons or remote sensing platforms. Combining miniaturized sensing systems with low mass, high drag structures (e.g., dandelion-inspired structures) allow for swarms of sensors to be deployed and carried passively by the wind. Adding functional materials into the system, such as shape memory alloys, allow for dynamic and controlled adjustment of drag characteristics, which can provide a certain degree of directional and lift control.
This effort will involve computational modeling and physical prototyping of elements of a dandelion seed-style drag structure, analytical modeling of flight characteristics under different atmospheric conditions, and development of control algorithms for the functional materials of the system to control its drag characteristics during its descent flight.
Navigation of Microgravity Surfaces Using Tethers
Exploration of the surfaces of asteroids (microgravity surfaces) will likely require a system of tethers that keep a spacecraft from bouncing into space due to low gravity. Many asteroids are simply loose piles of rubble, so tethers will need to be anchored to pitons buried under the surface rock. Robotic rovers will need to remain attached to these tethers while simultaneously traversing uneven, rocky terrain.
This effort will involve design, modeling, and prototyping of tether-guided rovers. Primary challenges will involve remaining attached to the tether while navigating uneven terrain and obstructions of all sizes. The goal of this project will be to demonstrate tethered locomotion over actual terrain that simulates lunar or asteroid surfaces.
Additive Manufacturing for Repair and Maintenance of Autonomous Systems
Additive Manufacturing also referred to as 3D printing, creates specialized designs and excessively intricate geometries. Such a new method of manufacturing has promising applications in repairing and maintaining of autonomous systems. Autonomous systems operate in complex, open-ended environments with a high level of independence and self-determination. In this project, AM will be used to fabricate or repair on site need it parts that are used in any autonomous systems.
This research allows for on-demand production of spare parts, reducing downtime, and increasing the system's operational efficiency and lifespan.
Additive Manufacturing to Reduce Autonomous Systems Weight
Weight plays a crucial role in the performance, efficiency, and functionality of autonomous machines. In this research the additive manufacturing will be used to reduce the weight of an autonomous system. The process of metal coating 3D-printed plastic parts has gained significant interest in the fields manufacturing and engineering. In this project, major heavy parts in an autonomous system will be 3D printed using ABS plastic then metal coated.
This research examines two different methods for metal coating 3D-printed plastic parts to be used in any autonomous system. Electroplating and epoxy coating as methods for strengthening 3D-printed components. The compressive, tensile strength, and overall resilience of each technique will be evaluated through comparative analysis.
