Autonomous Robotics

4 credits

Theory and application of algorithms and probabilistic techniques for autonomous robotics. Covers topics related to state estimation (Bayes filtering, probabilistic motion and sensor models), planning/control (search based planners, lattice based planners, trajectory following techniques), and perception and learning (object detection, learning from demonstrations etc.). Prerequisite: CSE 332; recommended: CSE 312; MATH 208.