ADVANCED ROBOTICS: MODERN MOTION PLANNING, ESTIMATION, AND CONTROL
Rigid body models of robots, constraints and contact, motion planning methods including sampling based, trajectory optimizations, state estimation algorithms including linear observers and filters, Kalman filters, optimization-based filters, feedback control methods including linear controls, Impedance Control, optimization-based controllers, Differential Dynamic Programming, Lyapunov Analysis and Design, and Underactuations. Knowledge of robotic systems [such as E C E/M E 439 and E C E/M E 441 ] is strongly recommended.
Prerequisites & course information
Requisites: Graduate/professional standing Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Learning Outcomes: 1. Describe the mathematical models of general robotic systems Audience: Graduate 2. Plan motion that realizes desired tasks Audience: Graduate 3. Estimate a robot’s state from available sensors Audience: Graduate 4. Control robot motion using appropriate controller designs Audience: Graduate Learning Outcomes: 1. Describe the mathematical models of general robotic systems Audience: Graduate 2. Plan motion that realizes desired tasks Audience: Graduate 3. Estimate a robot’s state from available sensors Audience: Graduate 4. Control robot motion using appropriate controller designs Audience: Graduate
Sources
- Course catalogue ↗2026-2027