Teaching

Term: Fall 2025 

Title: Planning, Learning, and Control for Autonomous Space Robots. 

Listing: ME-GY 7863 A, CSCI-GA 3033 7863

Content: This class will study the math and implementation of planning, learning, and control algorithms for aerospace robots. We will cover classical topics and emerging research areas in linear and nonlinear dynamics, optimal control, numerical optimization, Bayesian estimation, search-based planning, and reinforcement learning. We will study existing applications like precision rocket landings and martian rover path planning, and proposed future missions like distributed apertures of spacecraft swarms and complex locomotion for planetary exploration. 

Goals: The goals of the course are: (i) to build fundamental understanding of general robot autonomy with a focus on planning, learning, and control, (ii) to introduce applications in aerospace robotics and (iii) to prepare students to become researchers and devise novel methods and algorithms. 

Prerequisites: This class is targeted towards graduate-level students with familiarity in robotics, linear algebra, differential equations, probability, and Python programming. If you are unsure, feel free to contact me. 

Structure/Grading: TBD, most likely coding-assignments and project-based.