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| CS 55800 - Introduction To Robot Learning |
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Associated Term:
Spring 2024
Learning Outcomes: 1. Formulate the robot motion planning and control problems and solve them using standard tools. (W, P, E) 2. Identify the robot constraints, define their degree of freedom, and formulate their dynamical models for control. (W, P, E) 3. Apply classical and modern robot planning and control techniques to complex robot systems like manipulators, autonomous cars, etc. (W, P, E) 4. Identify limitations in existing classical robot algorithms and understand how to avoid the musing Machine Learning. (W, P) 5. Understand and apply Deep Reinforcement Learning approaches to complex robot systems. (W, P, E) 6. Evaluate and assess current best practices and mechanisms for robot programming. (W, P) 7. Develop a skill for robot programming from perception to low-level control using state-of-the art methods. (W, P) Required Materials: Technical Requirements: |
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