Introduction to robotics from a computational perspective covering AI foundations. Sensing and perception: state estimation challenges, such as robot localization, simultaneous localization and mapping (SLAM), Bayesian solutions, Kalman and particle filters, etc. Planning and decision making: basic planning and re-planning methods, A* and D*‐like algorithms, configuration space abstraction, sampling‐ based planners, etc. Multi‐robot systems: online planning and handling uncertainty. Control: introductory coverage of robot kinematics and dynamics.