Robotis Motion Planning
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Robotic Motion Planning
NSH 3002, MW10:30-11:50, Fall, 2010
Main
Syllabus
Lecture
Homework
Student Gallery
Reading Assignment</D\ iv>
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. Clickherefor 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
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- Robotis Motion Planning
- 《An Empirical Study of Optimal Motion Planning》
- 运动规划 (Motion Planning): MoveIt! 与 OMPL
- 运动规划 (Motion Planning): MoveIt! 与 OMPL
- ROS 运动规划 (Motion Planning): MoveIt! 与 OMPL
- ROS 运动规划 (Motion Planning): MoveIt! 与 OMPL
- Common motion planning algorithms 常用机器人运动规划算法
- ROS 运动规划 (Motion Planning): MoveIt! 与 OMPL
- Planning
- Planning
- Planning
- Planning
- Planning
- Planning
- 《Combined Task and Motion Planning Through an Extensible Planner-Independent Interface Layer》
- 2015-A Review 《Efficient Configuration Space Construction and Optimization for Motion Planning》
- 2015-《HG-RRT∗: Human-Guided Optimal Random Trees for Motion Planning》
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