Machine Learning for Robotics

Robot Learning - Spring 2025

Schedule

3/31/2025
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Course Opening
syllabus, logistics, high-level framework of embodied AI

Section I: Robot Embodiment and Classical Robotics

4/2/2025
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Control Architecture and Sensing
basic concepts of robotics and introduction to sensing
4/4/2025
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Coordinates, Frames, and Perception
basic concepts to describe geometric transformations useful for robotics
4/7/2025
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Motion Planning
basic concepts of robotics and introduction to sensing
4/9/2025
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Motion Planning Details and Trajectory Optimization
motion planning for high DoF systems
4/11/2025
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Acutation and Control
actuators and PID

Section II: Cognitive Basis of Embodied AI

4/14/2025
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Human's Sensorimotor System I
introduction to neural mechanisms
4/16/2025
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Human's Sensorimotor System II
introduction to neural mechanisms

Section III: Introduction to 2D and 3D Deep Learning

4/18/2025
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Deep Dive into 2D CNNs for Robotics
convnets, efficient 2D networks
4/21/2025
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Deep Dive into 3D Perception for Robotics
3D learning, pointnet, pointnet++, voxelnet, pointpillar
4/23/2025
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6D Object Pose Estimation I
Classical approach for 6D pose estimation
4/25/2025
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6D Object Pose Estimation II
Learning-based approaches for 6D pose estimation

Section IV: Reinforcement Learning

4/28/2025
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Fundamentals of Reinforcement Learning I
basic concepts of RL, MDP
4/30/2025
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Fundamentals of Reinforcement Learning II
value estimation, Q-learning

Section V: Decision Sequence Modeling

Section VI: Robot Data Strategies