Advanced Robot Learning for Planning and Control

3 credits · College of Engineering catalogue

Advisory Prerequisite: Undergraduate linear algebra and significant programming experience. Enforced Prerequisite: Graduate Standing. Credit Exclusions: Only one course may earn credit from ROB 429 and ROB 529. (3 credits) 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 reinforcement learning. Students implement the above learning algorithms on robots in simulation.