Course Outline
This course introduces students to localization, mapping, planning and control of mobile robots and self-driving cars from the probabilistic perspective. Topics include recursive state estimation, Gaussian filters, non-parametric filters, robot motion and perception, localization, mapping, SLAM (simultaneous localization and mapping), obstacle avoidance, navigation, and so on. Laboratory assignments provide hands-on experience with servo drives, sensors, interface circuitry, and microprocessor-based real-time control, Robot Operating System (ROS) programming. Students will fabricate working robotic systems in a group-based term project.