Open to Graduate and Advanced Undergraduate Students
Class Location: Carnegie 106
Class Time: 12:00 – 1:50 - Mondays and Thursdays
Instructor: Jeff Trinkle
Office: MRC 330c
Office Hours: 3:30-4:30 Wednesdays
Email: trinkle +AT+ gmail.com
Prerequisites: Algorithmic Robotics, Robotics I, or permission of instructor.
Other useful background: linear algebra
Description: This course introduces methods that leverage the basic techniques learned in Algorithmic Robotics and 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 and state space representations; combinatorial and sample-based planning methods; models of contact; grasp analysis; simulation of bodies in contact; and other relevant topics.
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) Peter Corke, Robotics, Vision, and Control: Fundamental Algorithms in Matlab, Springer Tracts in Advanced Robotics, 2011.
(3) R. Murray, Z. Li, and S. Sastry, A Mathematical Introduction to Robotic Manipulation, CRC Press, 1994.
(4) Howie Choset, et al, Principles of Robot Motion: Theory, Algorithms, and Implementations, MIT Press, 2005.
(5) M.T. Mason, Mechanics of Robot Manipulation, MIT Press, 2001.
Schedule: Lectures, Assignments, Due Dates