Course Syllabus
Zoom Link:
https://stanford.zoom.us/j/317185924?pwd=Z28rVFR5bStFRlR2QzBINVRhTGxSQT09
Password: cse348E
This course introduces technologies and mathematical tools for simulating, modeling, and controlling human/animal/robot movements. Students will be exposed to integrated knowledge and techniques across computer graphics, robotics, machine learning and biomechanics. The topics include numerical integration, 3D character modeling, keyframe animation, skinning/rigging, multi-body dynamics, human kinematics, muscle dynamics, feedback control, trajectory optimization, reinforcement/imitation learning for motor skills, and motion capture. Students who successfully complete this course will be able to use and modify physics simulator for character animation or robotic applications, to design/train control policies for locomotion or manipulation tasks on virtual agents, and to leverage motion capture data for synthesizing realistic virtual humans. The evaluation of this course is based on three assignments and an open-ended research project.
List of topics:
- Human kinematics
- Inverse kinematics
- Keyframe animation
- 3D orientation
- Numerical integration
- Rigid body simulation
- Contact and collision
- Articulated rigid bodies
- Feedback control
- Motion capture
- Optimal control
- Reinforcement learning
- Learning motor skills
- Muscles and skins
Recommended prerequisite: CS148 or CS205A.
Textbook: None. Course materials will be posted on Canvas.
Communication: Piazza.
Requirements: Students are expected to attend lectures, participate in class discussions and working sessions, and read the supplemental materials.
Assignments: There will be five programming projects in Python.
Late Policy: The grade on a late assignment will drop 10% for each day beyond the due date. A day ends exactly at 11:59pm. No late assignments will be accepted four days or later after the date that the assignment was due.
Exam: None.
Course Summary:
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