EECS 465
Introduction to Algorithmic Robotics
An introduction to the algorithms that form the foundation of robot planning, state estimation, and control. Topics include optimization, motion planning, representations of uncertainty, Kalman and particle filters, and point cloud processing. Assignments focus on programming a robot to perform tasks in simulation.
Topics
- optimization
- motion planning
- representations of uncertainty
- Kalman and particle filters
- and point cloud processing
Topics explicitly listed in official catalogue description
Prerequisites & course information
[EECS 280 and MATH 215; (C or better, No OP/F) and (Junior or Senior Standing)] or Graduate Standing. (Prerequisites enforced at registration.) EECS 281 and (MATH 214 or MATH 217 or MATH 417 or MATH 419 or ROB 101) or permission of instructor. (BS). May not be repeated for credit.
Sources
- Course catalogue ↗2026-2027
- Catalogue entry ↗
Catalogue variants
- Introduction to Algorithmic Robotics · Graduate credit