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CSE 468LR Robotics Algorithms
Computer Science & Engineering

This course will study key algorithms relevant to programming intelligent robots with a focus on the following questions: How might one program a robot to estimate the state of the world based on multiple sources of information? How might a robot create plans or control policies for performing tasks? How might a robot learn a control policy directly from experience? The course will cover topics in estimation, control, and planning with applications to robotics including: reinforcement learning, linear optimal control, randomized motion planning, trajectory optimization, Kalman filtering, particle filtering, and selected topics in optimization.

Credits: 4
Semester(s) Typically Offered: Fall, Spring
Grading: Graded (GRD)
Pre-Requisites: CSE 250 or EAS 230 and EAS 305 or MTH 411 or STA 301; Computer Science, Computer Engineering, or Bioinformatics-CS majors only.

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