# Robotic Manipulation: Analysis and Algorithms

 No image available, but click "Dynamic manipulation" for a cool video No image available, but click "Bulldogs are best" for an amazing manipulation video Quasistatic manipulation Dynamic manipulation Bulldogs are best

Instructor: Jeff Trinkle
Office: MRC 330c (mornings), Lally 209b (afternoons)
Email: trink AT cs.rpi.edu

Class Location: MRC 334
Class Time: MR 2:00 – 3:50
Office Hours: T 1:00 – 2:00, F 2:00-3:00, or by appointment
Lab Location: MRC rooms 331, 332, 345, 352

Prerequisites: PHYS 1100 and Math 1020 or permission of the instructor.

Goal: One of the most compelling visions in the field of robotics, is the intelligent dexterous robot that can relieve humans of many manual tasks such as folding laundry, framing a house, or repairing a car engine. Unfortunately today's robots are notoriously inept at manipulation tasks - tasks that cannot be done without contact between the robot and moveable objects in the environment. The goal of this course is to develop a fundamental understanding of manipulation through the study of mathematical models of manipulation and algorithms that use these models to plan manipulation tasks.

Text: M.T. Mason, "Mechanics of Robot Manipulation," MIT Press, 2001.  Errata.

Description: Manipulate: "To move, arrange, operate, or control by the hands or by mechanical means, especially in a skillful manner." (taken from dictionary.com). Examples of manipulation include moving, joining, grinding, bending, and reshaping objects. While the first form of manipulation would arguably be the easiest to perform, it is still very difficult for robots. As a result, the majority of manipulation research in robotics still focuses on "simple" tasks that require moving a single nominally rigid object. Therefore, this course will focus on the fundamental concepts of manipulation, including kinematic manipulation, friction, quasi-static manipulation, impact, and dynamic manipulation. We will also study how one can combine the mathematical representations of these concepts with search techniques to yield manipulation planning algorithms.

The concepts covered in this course are also fundamental to physically-based graphics and animation, haptic interaction with virtual worlds, and certain aspects of mechanical design.

·  16-741: Matt Mason’s course page at CMU.

·  MEAM 520: Notes from Vijay Kumar's course, Automation and Robotics."

·  Acroname: Makers of the mobile robot you can use for a project in this class.

·  Wikipedia: A public encyclopedia of mathematics.

·  Mathworld: A public encyclopedia of mathematics.

·  Andrew Miller's GraspIt: Code for grasp analysis and planning.

Acknowledgements Thanks to Matt Mason for writing the text I'm using for this class and for sharing slides, videos, pictures, notes, and most importantly, his thoughts on the many questions I've asked. Thanks also to Makoto Kaneko, Dan Koditschek, and Ken Salisbury who have provided video clips to illustrate concepts and capture imaginations.