RESEARCH NEWS
VODCA Lab: Physics-Informed Learning for Safe
SRGE Lab: AI for Space Robotics and Lunar Operations Dr. Cagri Kilic The Space Robotics and Generative Estimation (SRGE) Lab applies AI and machine learning to robotics and space systems. The lab’s research connects perception, estimation and control for autonomous robotic platforms operating in complex environments. Current projects include machine learning for robotic state estimation, reinforcement learning for locomotion and interaction and AI-assisted space weather monitoring using solar imagery. Through a NASA Florida Space Grant Consortium project, the lab also develops AI-based methods for lunar terrain characterization and mobility planning. These efforts focus on improving localization, mapping and hazard detection under uncertain surface conditions, supporting future lunar exploration missions.
Spacecraft Autonomy Drs. Anouck Girard (Embry-Riddle) and Ilya Kolmanovsky (University of Michigan)
The Vehicle Optimization, Dynamics, Control and Autonomy (VODCA) Lab develops learning-based approaches for safe and autonomous spacecraft operations in uncertain environments. Their research reduces onboard computational burden while maintaining physical consistency — a key requirement for real-time autonomy. One major contribution is the temporal Hamiltonian Neural Network, which learns unknown dynamical systems while preserving physical invariants such as energy. This structure improves state estimation accuracy when paired with adaptive Kalman filtering. The lab also develops Constraint-Informed Neural Networks (CINNs) that integrate advanced neural architectures with constraint enforcement mechanisms to ensure safety and computational efficiency. These methods have been validated in spacecraft state estimation and rendezvous problems on elliptic orbits.
DEPARTMENT OF AEROSPACE ENGINEERING | 3
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