Robotis Motion Planning

RI16-735
Robotic Motion Planning
NSH 3002, MW10:30-11:50, Fall, 2010

 

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Reading Assignment

Personnel:	Instructor: Howie Choset, NSH 3211 choset [theat] cs [thedot] cmu [thedot] edu 412-CMU-2495 TA: Glenn Wagner, NSH A403 (temporary) gswagner [theat] cmu [thedot] edu 412-CMU- Mailing List: Secretary: Peggy Martin NSH 3218 pm1e [theat] andrew [thedot] cmu [thedot] edu 412-CMU-7943 Class group email (Email TA to be added/removed) 16735-f10 [theat] googlegroups [thedot] edu
Descriptive Blurb:	The robot motion field and its applications have become incredibly broad and theoretically deep at the same time. The goal of the course is to provide an up-to-date foundation in the motion planning field, make the fundamentals of motion planning accessible to the novice and relate low-level implementation to high-level algorithmic concepts. We cover basic path planning algorithms using potential functions, roadmaps and cellular decompositions. We also look at the recent advances in sensor-based implementation and probabalistic techniques, including sample-based roadmaps, rapidly exploring random trees, Kalman filtering, and Bayesian estimation. If time permits, we will study non-linear controls and how it applies to non-holonomic constraints. Click here for more information.
Who should take this class:	Advanced undergraduates and graduate students who are new to motion planning.
Text:	H. Choset, K. M. Lynch, S. Hutchinson, G. Kantor, W. Burgard, L. E. Kavraki and S. Thrun, Principles of Robot Motion: Theory, Algorithms, and Implementations, MIT Press, Boston, 2005. Errata
Related Robotics Texts:	Robot Motion Planning,  Jean-Claude Latombe,  Kluwer Academic Publishers, 1991. Planning Algorithms, Steven M. LaValle. Probabilistic Robotics, S. Thrun, W. Burgard, and D. Fox, MIT press, Cambridge, MA, 2005 Where am I?--Sensors and Methods for Mobile Robot Positioning by J. Borenstein , H. R. Everett , and L. Feng Introduction to AI Robotics by Robin Murphy Sensors for Mobile Robots by H. Bart R. Everett Computational Principles of Mobile Robotics by Gregory Dudek and Michael Jenkin Feedback Systems: An Introduction for Scientists and Engineersby Karl J. Astrom and Richard M. Murray
Papers:	Here is a far-from updated list of papers for your reference Follow the Book Outline Bob Grabowski's Favorites Latombe's List of Researchers Goldberg's List from his class Srinivas Akella's List
Homework:	You are required to create a web page on which you will display your homework assignments. This page should contain a link to each homework's solution. The page for an individual assignment should include a demo of the working program (e.g., gif files, animations), links to source code for your programs (including any necessary makefiles, and a brief explanation of your approach.
Class Project:	Propose and implement a robot motion planning project. It can be something related to your research and it must have a motion planning component to it (respect obstacles).   Project proposals will be due at mid-semester (deadlines will be announced soon, and here is a PPT template). As with your homework,  you will create a web page for your project, and it is this web page that will be graded. This page is due 12/12 (two days after the demo) at midnight. You may find this collection of laser scan data helpful.
Reading Assignment:	Based on your interests, we will form groups of one or two to present a paper that go into depth a topic which was covered in the previous week.
Grading	70% Homework 10% Reading presentation 20% Final project
Software: (No Guarantees)	Please feel free to use software resources that are available in the public domain such as Kavraki Lab's OOPSMP  Mitul's Motion Planning Tool Kit  OpenGL  CGAL homepage  LEDA homepage  GIFMerge homepage  Collision Detection: RAPID, PQP, V-COLLIDE, I-COLLIDE  Collision Detection: V-Clip  Geomview  Source Forge Nomadic Software  Dave's Robotic Operating System  Pyro, Prthon Robotics  The Orocos project  Robot Intelligent Kernel  Marie  Orca: components for Robotics  Experimental robotics framework  Microsoft Robotics Studio  Robomind  OpenRAVE  RoS