Research outputs
2026
From nature to robots: a comprehensive survey on lizard-inspired robotics for ground and space exploration
Das, G., Vera, A., Choi, D., Chhabra, A., Kim, D., & Jayne, B. (2026). From nature to robots: a comprehensive survey on lizard-inspired robotics for ground and space exploration. BIOINSPIRATION & BIOMIMETICS, 21(2). doi:10.1088/1748-3190/ae2b18
DYNAMOS: Design, Implementation, and Validation of a Hardware-in-the-Loop Simulation Testbed for In-Space Servicing
Chhabra, A., & Kim, D. (2026). DYNAMOS: Design, Implementation, and Validation of a Hardware-in-the-Loop Simulation Testbed for In-Space Servicing. IEEE Aerospace and Electronic Systems Magazine, 1-11. doi:10.1109/maes.2026.3656844
2025
Design and Development of a Spacecraft Simulator for Hardware-In-the-Loop Simulation of In-space Servicing, Assembly, and Manufacturing Missions
Chhabra, A. (2025, December 4). Design and Development of a Spacecraft Simulator for Hardware-In-the-Loop Simulation of In-space Servicing, Assembly, and Manufacturing Missions. (University of Cincinnati).
Development of a Reconfigurable Space Manipulator Testbed for Dynamic Coupling Analysis
Chhabra, A., Das, G., Quevedo, D., Choi, D., & Kim, D. (2025). Development of a Reconfigurable Space Manipulator Testbed for Dynamic Coupling Analysis. In NAECON 2025 - IEEE National Aerospace and Electronics Conference (pp. 1-6). IEEE. doi:10.1109/naecon65708.2025.11235454
2023
Fuzzy Inference System-Applied Spacecraft Control for Final Approach of Rendezvous Process
Choi, D., Chhabra, A., & Kim, D. (2023). Fuzzy Inference System-Applied Spacecraft Control for Final Approach of Rendezvous Process. In 2023 23rd International Conference on Control, Automation and Systems (ICCAS) (pp. 1401-1406). IEEE. doi:10.23919/iccas59377.2023.10316839
2022
Ground Robotic Platform for Simulation of On-Orbit Servicing Missions
Chhabra, A., & Kim, D. (2022). Ground Robotic Platform for Simulation of On-Orbit Servicing Missions. JOURNAL OF AEROSPACE INFORMATION SYSTEMS. doi:10.2514/1.I011008
Intelligent cooperative collision avoidance via fuzzy potential fields
Choi, D., Chhabra, A., & Kim, D. (2022). Intelligent cooperative collision avoidance via fuzzy potential fields. ROBOTICA, 40(6), 1919-1938. doi:10.1017/S0263574721001454
Collision Avoidance of Unmanned Aerial Vehicles Using Fuzzy Inference System-Aided Enhanced Potential Field
Choi, D., Chhabra, A., & Kim, D. (2022). Collision Avoidance of Unmanned Aerial Vehicles Using Fuzzy Inference System-Aided Enhanced Potential Field. In AIAA SCITECH 2022 Forum. American Institute of Aeronautics and Astronautics. doi:10.2514/6.2022-0272
2021
Measurement Noise Covariance-Adapting Kalman Filters for Varying Sensor Noise Situations
Chhabra, A., Venepally, J. R., & Kim, D. (2021). Measurement Noise Covariance-Adapting Kalman Filters for Varying Sensor Noise Situations. SENSORS, 21(24). doi:10.3390/s21248304
Genetic Algorithm-Aided Fuzzy Controller for Spacecraft Attitude Maneuver with Uncertainties
Choi, D., Chhabra, A., & Kim, D. (2021). Genetic Algorithm-Aided Fuzzy Controller for Spacecraft Attitude Maneuver with Uncertainties. In ASCEND 2021. American Institute of Aeronautics and Astronautics. doi:10.2514/6.2021-4174
Decentralized Collision Avoidance via Fuzzy Potential Fields
Chhabra, A., Choi, D., & Kim, D. (2021). Decentralized Collision Avoidance via Fuzzy Potential Fields. In NAECON 2021 - IEEE National Aerospace and Electronics Conference (pp. 33-39). IEEE. doi:10.1109/naecon49338.2021.9696428
2020
Identifying Factors in COVID-19 AI Case Predictions
Pickering, L., Viana, J., Li, X., Chhabra, A., Patel, D., & Cohen, K. (2020). Identifying Factors in COVID-19 AI Case Predictions. In 2020 7TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING & MACHINE INTELLIGENCE (ISCMI 2020) (pp. 192-196). Retrieved from https://www.webofscience.com/
Understanding the Effects of Human Factors on the Spread of COVID-19 Using a Neural Network
Chhabra, A., Patel, D., Li, X., Pickering, L., Viana, J., & Cohen, K. (2020). Understanding the Effects of Human Factors on the Spread of COVID-19 Using a Neural Network. In 2020 7TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING & MACHINE INTELLIGENCE (ISCMI 2020) (pp. 121-125). doi:10.1109/iscmi51676.2020.9311591