Robot Learning for Planning and Control
Graduate course, University of Michigan, Robotics, Winter 2023
An introduction to modern machine learning methods for control and planning in robotics. Topics include function approximation, learning dynamics, using learned dynamics in control and planning, handling uncertainty in learned models, learning from demonstration, and model-based and model-free reinforcement learning. Students implement the above learning algorithms on robots in simulation.
