Difference between revisions of "Path Planning Systems"

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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 of the "Data Filtering Systems."
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The "Path Planning Systems" groups is responsible for 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, maps, and learning are the main focus points of this group.
  
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[[Image:igvcpp.png|thumb|right|480px|Path Planning Systems Architecture]]
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== People ==
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* [[User:JeanPierreDLC|JP]]
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* [[User:JinL|Jin Joo]]
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* [[User:HusaynV|Husayn]]
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== Meetings ==
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* IGVC Planning Day
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** Tuesday, 6-7pm, Tin Building
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* Path Planning Meeting (with Dr. Vela)
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** Friday, 1pm, Van Leer (VL) E368
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* IGVC Work Day
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** Saturday, 2-6pm, Tin Building
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== TODO List ==
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* [ ] Week of January 28, 2008
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** [ ] MATLAB
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*** [ ] Vectorization
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*** [ ] Splines
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** [ ] C
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*** [ ] Matrices/Vectors
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**** [ ] MTL http://osl.iu.edu/research/mtl/
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**** [ ] Meschach http://www.math.uiowa.edu/~dstewart/meschach/
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**** [ ] FLENS http://flens.sourceforge.net/
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*** [ ] Data Structures
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**** [ ] Stack
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**** [ ] Occupancy Grid
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***** [ ] Grid Point
  
 
== Task List ==
 
== Task List ==
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* [ ] Research different types of path planning algorithms
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* [ ] Path Planning
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* [ ] Determine relevant algorithms
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** [x] Dijkstra's algorithm
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** [ ] for autonomous navigation challenge
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** [ ] Gradient traversal
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** [ ] for GPS waypoint navigation challenge
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*** [x] manhatten distance
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* [ ] Research control theory
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*** [x] vector addition
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** [ ] Optimal switching
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*** [ ] splines
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* [ ] Determine best type of map (representation of environment)
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** [ ] A* algorithm
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** [ ] Coordinate with "Data Filtering Systems" group
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** [ ] D* algorithm
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* [ ] Cost Map
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** [x] Sweeping Algorithm
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*** [x] implement manhattan distance
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*** [x] implement geometric approximation
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*** [x] add obstacles
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*** [x] add variable start/goal locations
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** [ ] Obstacle Avoidance
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*** [ ] using sweeping algorithm
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*** [ ] using depth-limited sweep
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* [ ] Implementation
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** [ ] Matlab Prototype
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** [ ] C/C++ Product
  
 
== Resources ==
 
== Resources ==
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=== Books ===
 
* "Planning Algorithms" by Steven M. LaValle
 
* "Planning Algorithms" by Steven M. LaValle
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**http://planning.cs.uiuc.edu
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** http://planning.cs.uiuc.edu
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** [[User:JinL|Jin Joo]] has a hard copy.
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* "Probabilistic Robotics" by Sebastian Thurn, Wolfram Burgard, Dieter Fox
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** [[User:JeanPierreDLC|JP]] has a hard copy.
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=== Articles ===
 
* IEEE Xplore
 
* IEEE Xplore
 
**http://www.library.gatech.edu:2048/login?url=http://ieeexplore.ieee.org
 
**http://www.library.gatech.edu:2048/login?url=http://ieeexplore.ieee.org
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* Lengyel, Reichert, Donald, and Greenberg. "Real-Time Robot Motion Planning Using Rasterizing Computer Graphics Hardware." Comp. Graph., Vol. 243, No. 4, pp. 327-335, 1990.
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**http://www.cs.dartmouth.edu/~brd/papers/siggraph/animation.pdf
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* Kimmel and Sethian. "Optimal Algorithm for Shape from Shading and Path Planning." J. of Math. Imaging and Vis., Vol 14, pp. 237-244, 2001.
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**http://www.cs.technion.ac.il/~ron/PAPERS/optimal_shading2001.ps.gz
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* Wiener and Mallot. 'Fine-to-Coarse' Route Planning and Navigation in Regionalized Environments. Max-Planck-Institute Biological Cybernetics. Technical Report TR-115, 2003.
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**http://wiki.robojackets.org/wiki/images/f/f2/WienerMallot.pdf
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* Kuffner. Efficient Optimal Search of Uniform-Cost Grids and Lattices. Proceedings IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004. 1946-1950.
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**http://wiki.robojackets.com/wiki/images/e/eb/KuffnerOptimalSearch.pdf
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* Hassouna, Abdel-Hakim, Farag. "Robust Robotic Path Planning Using Level Sets." Proc. IEEE ICIP, pp 473-476, 2005.
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**http://www.cs.dartmouth.edu/~brd/papers/siggraph/animation.pdf
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[[Category: IGVC]][[Category:2008-2009]]

Latest revision as of 21:05, 18 July 2018

The "Path Planning Systems" groups is responsible for 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, maps, and learning are the main focus points of this group.

Path Planning Systems Architecture

People

Meetings

  • IGVC Planning Day
    • Tuesday, 6-7pm, Tin Building
  • Path Planning Meeting (with Dr. Vela)
    • Friday, 1pm, Van Leer (VL) E368
  • IGVC Work Day
    • Saturday, 2-6pm, Tin Building

TODO List

Task List

  • [ ] Path Planning
    • [x] Dijkstra's algorithm
    • [ ] Gradient traversal
      • [x] manhatten distance
      • [x] vector addition
      • [ ] splines
    • [ ] A* algorithm
    • [ ] D* algorithm
  • [ ] Cost Map
    • [x] Sweeping Algorithm
      • [x] implement manhattan distance
      • [x] implement geometric approximation
      • [x] add obstacles
      • [x] add variable start/goal locations
    • [ ] Obstacle Avoidance
      • [ ] using sweeping algorithm
      • [ ] using depth-limited sweep
  • [ ] Implementation
    • [ ] Matlab Prototype
    • [ ] C/C++ Product

Resources

Books

  • "Planning Algorithms" by Steven M. LaValle
  • "Probabilistic Robotics" by Sebastian Thurn, Wolfram Burgard, Dieter Fox
    • JP has a hard copy.

Articles

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