Difference between revisions of "ME CS 132 2017"
(→Course Lecture Schedule for ME/CS 132(a))
m (→Graphs Search (continued), Sensor-Based Motion Planning)
|Line 175:||Line 175:|
| 15 Feb (W)
| 15 Feb (W)
| A-Star & Dijkstra Graph Search <br> Bug Algorithms
| A-Star & Dijkstra Graph Search <br> Bug Algorithms
| [[Media:Astar.pdf | Notes on A-star]]; [[Media:
| [[Media:Astar.pdf | Notes on A-star]]; [[Media:.pdf | Analysis of A-] <br> [[Media:BugSlides.pdf | Choset Slides on Bug Algorithms ]] <br> Lavalle 667-673
Revision as of 19:33, 15 February 2017
This is the homepage for ME/CS 132(a,b) (Advanced Robotics: Navigation and Vision) for Winter/Spring 2017.
Course Staff, Hours, Location
|Position||Name||Office||Office Hours (changing weekly)||Phone|
|Instructor||Joel Burdick||245 Gates-Thomas||send mail for an appointment||jwb at robotics dot caltech dot edu||626-395-4139|
|Teach Asst.||Joseph Bowkett||205 Gates-Thomas||Wed 2/15 6-7pm SFL 220 & Thurs 2/16 4-5:30pm SFL 231||jbowkett at caltech dot edu||626-395-1989|
|Teach Asst.||Daniel Pastor Moreno||205 Gates-Thomas||TBD||dpastorm at caltech dot edu||626-395-1989|
|Teach Asst.||Yoke Peng Leong||Annenberg||TBD||ypleong at caltech dot edu||626-395-????|
|Administrative||Sonya Lincoln||250 Gates-Thomas||7:30am-noon; 1:00pm-4:30pm||lincolns at caltech dot edu||626-395-3385|
Lecture Schedule: Based on a vote in class, for the near future we will meet at these times and locations:
- Wednesday: 7:30-10:30 pm. Room 135 Gates-Thomas
Note: As the course enrollment firms up, we will vote one more time to see if we can find a better meeting time.
Announcements For ME/CS 132(a,b)
- 02/13/17: Office Hours for Homework #3 will be held 6-7 pm on Wed., Feb 15 in 220 SFL, and 4:00-5:30 pm on Thurs., Feb 16 in 231 SFL
- 02/01/17: Office Hours for Homework #2 will be held 7:30-9:00 pm on Thurs., Feb. 1 in 135 Gates-Thomas
- 01/22/17: Office Hours for Hmmeowrk #1 will be held 8-10 pm on Sunday, Jan. 22 in 135 Gates-THomas.
- 01/05/17: The meeting time and place have been set for the class lectures.
- 01/04/17: The permanent lecture hours and location will be determined at the course organizational meeting.
Course Text and References
1) The main text for the first half of the course is:
- Planning Algorithms by Steve LaValle (UIUC).
2) The following book is recommended (but not required):
- Principles of Robot Motion: Theory, Algorithms, and Implementations, by Howie Choset, Kevin Lynch, Seth Hutchinson, George Kantor, Wolfram Burgard, Lydia Kavraki, and Sebastian Thrun.
This text is available at Amazon in both new and used versions.
3) Interested students may wish to also consult the following classic (but now out-of-print) text on motion planning: Robot Motion Planning by J.C. Latombe. A copy is available in the Caltech library.
Course Lecture Schedule for ME/CS 132(a)
Introduction and Review of Rigid Body Kinematics
|4 Jan (Wed.)|| Class Overview & Mechanics
The basic motion planning problem
|Course Overview||Chapter 1 of Lavalle||-No Homework-|
|6 Jan (Fri.)||Review of Motion Planning Problems and Issues|
Intro to C-space and the Basic Motion Planning Problem
|11 Jan (W)|| Configuration Space (C-space)
Review of Planar Rigid Body Kinematics
| Lavalle 4.2.1; Lavalle Chapter 3.2.2 (pages 94-97)
Notes on C-obstacles; The Star Algorithm;
| MLS Ch 2.1, Pages 19-23
Lavalle Chapter 3.1
| Homework 1, |
|13 Jan (F)||Configuration-Space Obstacles|| Lavalle Chapter 4.3
Notes on Parametrized C-obstacles
|Picture of C-Obstacle; C-space Visualization Video;Mathematica Demo of Manipulator C-Obstacles;|
C-obstacles and the Classical Motion Planning Algorithms
|18 Jan (W)|| Computing C--space obstacles
Review of Classical Motion Planning Algorithms
The Road Map
| Lavalle 4.3 (pages 155-167)
Lavalle 6.1, Lavalle 6.2 (focusing on roadmaps)
|No Homework Assigned|
Roadmap Motion Planning Algorithms
|25 Jan (W)|| The Road Map (continued)
Intro to Potential Field Methods
|Lavalle 6.1, Lavalle 6.2 (focusing on roadmaps)|| Homework #2 |
Instructions for OMPL and ROS Virtual Machine Setup
Potential Field and Cellular Decomposition Algorithms
|1 Feb (W)|| Potential Fields continued
Cellular Decomposition Methods
|Lavalle 6.3 (Cellular Decompositions)||No Homework Assigned|
Sampling Based Methods and Graphs Search Algorithms
|8 Feb (W)|| Sampling Based Planning Methods
Brief Tutorial on Graph Searching
| Lavalle, Sections 5.2-5.5 (Samplinlg Based Methods)
Lavalle, Section 2.1 and 2.2
Notes on A-star
| Homework #3 |
Instructions for Lab 2
Files for Lab 2
Graphs Search (continued), Sensor-Based Motion Planning
|15 Feb (W)|| A-Star & Dijkstra Graph Search
| Notes on A-star; Analysis of A-Star
Choset Slides on Bug Algorithms
Course Mechanics, Grading, and Collaboration Policy
The final grade will be based on homework sets, and a final exam or final project:
- Homework (70%): Homework sets will be handed out every 7-10 days, and are due at 5 pm on the due date (which will always coincide with a class meeting). Homeworks can be dropped off in class, or deposited in the box outside of 245 Gates-Thomas. Some homeworks will require computation. MATLAB or Mathematica should be sufficient to solve every homework posed in this course, though students can choose their favorite programming language. Code is considered part of your solution and should be included in with the problem set when appropriate.
- Final exam/project (30%): Students have the option to take a final exam (a limited time take-home format exam which is open book, open note, and computer allowed) or select a final project. The final project must incorporate some aspect of the course, and the topic and scope my be approved by the course instructor. The final exam will due at 5:00 pm the last day of finals. The final project is similarly due at 5:00 pm on the last day of finals.
- Late Homework Policy: Students may automatically take a 2-day extension on two homeworks during each quarter.
Collaboration on homework assignments is encouraged. You may consult outside reference materials, other students, the TA, or the instructor, but you must cite any use of material from outside references. All solutions that are handed in should be written up individually and should reflect your own understanding of the subject matter. Computer code and graphical plots are considered part of your solution, and therefore should be done individually (you can share ideas, but not code). No collaboration is allowed on the examinations.