This course teaches advanced principles for endowing mobile autonomous robots with capabilities to autonomously learn new skills and to physically interact with the environment and with humans. It also provides an overview of different robot system architectures. 

Topics Include

  • Reinforcement Learning and its relationship to optimal control
  • Contact and dynamics models for prehensile and non-prehensile robot manipulation,
  • Imitation learning and human intent inference
  • Different system architectures and their verification

You will learn the theoretical foundations for these concepts and implement them on simulated mobile manipulation platforms. In homework, the Robot Operating System (ROS) will be used extensively for demonstrations and hands-on activities.

Please note that this course is cross listed with AA274B.