Open to Graduate and Advanced Undergraduate Students
Class Location: Sage 2704
Class Time: 10:00 – 11:50 Tuesdays and Fridays
Robotics Lab Location: MRC room 331
Instructor: Jeff Trinkle
Office: MRC 330c
Office Hours: Mondays and Thursdays 2:30-3:45
Email: trink AT cs.rpi.edu
Prerequisites: Robotics I or permission of instructor.
Other useful background: linear algebra, optimization
Description: This course introduces methods that leverage the basic analysis techniques learned in Robotics I to develop numerical and algorithmic techniques needed to endow robots with the “intelligence” to devise strategies to solve problems they will encounter. Once these abilities are sufficiently well developed, robots will become safe and autonomous, thus paving the way for pervasive personal robots. Topics include: configuration space representation, cell decomposition, roadmap methods, rapidly-exploring random trees, contact modeling, grasping, dexterous manipulation, and other current topics.
Required text:
Steve M. LaValle,
Planning Algorithms, Cambridge
University Press, 2006. Available free at
http://planning.cs.uiuc.edu/.
Other useful texts:
(1) Prattichizzo and Trinkle, ``Grasping," in Springer Handbook of Robotics, Siciliano and Khatib, editors, Springer-Verlag, 2008.
(2) Howie Choset, et al, Principles of Robot Motion: Theory,
Algorithms, and Implementations, MIT Press, 2005.
(3) M.T. Mason, Mechanics of Robot
Manipulation, MIT Press, 2001.
Lectures
Policies
Grading
Assignments
Project Ideas
Hints
Useful links
da Vinci Code: Planar multibody dynamics simulator develop in the CS Robotics Lab.
Barrett Technologies: Maker of the Arm and Hand in the CS Robotics Lab.
Andrew Miller's GraspIt! Code for grasp analysis and planning.