Course Websites

Subject offerings of new and developing areas of knowledge in aerospace engineering intended to augment existing formal courses. Topics and prerequisites vary for each section. See Class Schedule or departmental course information for both. Course Information: May be repeated in the same or separate terms if topics vary to a maximum of 12 hours.

Topic: Spacecraft Rendezvous and Proximity Operations. This course provides a comprehensive treatment of spacecraft rendezvous, proximity operations, and docking (RPO), with a primary emphasis on autonomous trajectory design and guidance, navigation, and control (GNC). Students develop a rigorous understanding of relative motion dynamics, rendezvous and proximity trajectory design, and closed-loop guidance and navigation under realistic constraints in sensing, actuation, and operational implementation. Classical impulsive and low-thrust rendezvous methods are integrated with contemporary optimization-based guidance and safety-critical constraint enforcement. The course also introduces enabling autonomy topics that increasingly shape modern RPO systems, including perception-driven proximity operations, robotic capture and grasping in microgravity, teleoperations, and verification and validation of RPO. Prerequisites: AE 402, AE 353 (or equivalent), AE 454 (or equivalent), AE 485 (option

This course presents advanced formal methods for providing performance guarantees in motion planning and control (guidance and control) of nonlinear dynamical systems under uncertainty, with a special focus on aerospace and robotic systems. Topics include a review of robotics and optimal control, robust and adaptive control, safe planning and control, risk-aware planning and control, uncertainty quantification, safe reinforcement learning, learning-based/data-driven planning and control, applications in aerospace and robotic systems, and a final project. The themes of the final project will be given, but students are welcome to work on their own ideas.

4 hours

Undergraduate degree and statistics (STAT 361, STAT 400, or MATH 461), robotics (AE 482, ECE 470, or ME 445), and feedback control (AE 454 or ECE 486), or permission of instructor. It is desirable also to have some basics of optimal control (AE 504 or ECE 515).