CS 6751 - Robot Manipulation

(crosslisted) MAE 6730

Spring. 3 credits. Letter grades only.

Prerequisite: Proficiency in C++ or Python, and familiarity with ROS. Intended for: graduate students, or permission of the instructor. Recommended prerequisite: for undergraduates: MAE 4180 or CS 4750/ECE 4770/MAE 4760/CS 5750. For the CS Ph.D. breadth requirement, this course counts as the AI area with either the systems or applied research style.

T. Bhattacharjee.

Robot manipulation is the ability for a robot to interact physically with objects in the world and manipulate them towards completing a task. It is one of the greatest technical challenges in robotics, due primarily to the interplay of uncertainty about the world and clutter within it. As robots become integrated into complex human environments, robot manipulation is increasingly necessary to assist humans in these unstructured environments. Robotic manipulation will enable applications like personal assistant robots in the home and factory worker robots in advanced manufacturing. This course is a mixture of lectures and paper presentations and covers the fundamental theory, concepts, and systems of robot manipulation, including both software and hardware. Topics we will cover this semester include perception, state estimation, robot arm kinematics and dynamics, task and motion planning, machine learning, controls, human-robot interaction towards various robot manipulation tasks. The course features a semester-long group project in which students propose, formalize, and execute a working robotic manipulation system towards a real-world task. The scope of possible components is quite broad and extends beyond traditional robotics issues into other aspects of CS. This course is offered to prepare a student for Ph.D. research in robot manipulation.