Difference between revisions of "Path Planning Systems"
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(→Resources: Added additional resource.) |
(→Task List: Updated tasks.) |
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== Task List == | == Task List == | ||
* [ ] Research different types of path planning algorithms | * [ ] Research different types of path planning algorithms | ||
+ | ** [ ] Add relevant resources to the "Resources" section. | ||
* [ ] Determine relevant algorithms | * [ ] Determine relevant algorithms | ||
** [ ] for autonomous navigation challenge | ** [ ] for autonomous navigation challenge |
Revision as of 18:47, 18 September 2007
The purpose of the "Path Planning Systems" is to find an optimal path through the environment, given a model of the environment from the data (provided by Data Filtering Systems group). This group will be developing the high-level code to control Candii during the autonomous and GPS waypoint navigation challenges--essentially, Candii's AI. Path planning algorithms, optimal switching, and maps are the main focus points of this group.
Task List
- [ ] Research different types of path planning algorithms
- [ ] Add relevant resources to the "Resources" section.
- [ ] Determine relevant algorithms
- [ ] for autonomous navigation challenge
- [ ] for GPS waypoint navigation challenge
- [ ] Research control theory
- [ ] Optimal switching
- [ ] Determine best type of map (representation of environment)
- [ ] Coordinate with Data Filtering Systems group
Resources
- "Planning Algorithms" by Steven M. LaValle
- IEEE Xplore
- Wiener and Mallot. 'Fine-to-Coarse' Route Planning and Navigation in Regionalized Environments. Max-Planck-Institute Biological Cybernetics. Technical Report TR-115, 2003.
- Kuffner. Efficient Optimal Search of Uniform-Cost Grids and Lattices. Proceedings IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004. 1946-1950.