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CS 326 A: Motion Planning Probabilistic Roadmaps Basic Techniques.

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Presentation on theme: "CS 326 A: Motion Planning Probabilistic Roadmaps Basic Techniques."— Presentation transcript:

1 CS 326 A: Motion Planning http://robotics.stanford.edu/~latombe/cs326/2003 Probabilistic Roadmaps Basic Techniques

2 Motivation Geometric complexity Space dimensionality

3 Weaker Completeness  Complete planner  Too slow  Heuristic planner  Too unreliable  Probabilistic completeness: If there is a solution path, the probability that the planner will find is a (fast growing) function that goes to 1 as running time increases

4 Initial idea: Potential Field + Random Walk

5 But Pathological Cases …

6 Probabilistic Roadmap (PRM) free space mbmbmbmb mgmgmgmg milestone [Kavraki, Svetska, Latombe,Overmars, 95] local path

7 Single-Query PRM Planning mbmbmbmb mgmgmgmg

8 Two Tenets of PRM Planning Checking sampled configurations and connections between samples for collision can be done efficiently.  Hierarchical collision checking A relatively small number of milestones and local paths are sufficient to capture the connectivity of the free space.  Exponential convergence in expansive free space (probabilistic completeness)

9 Second Tenet of PRM Planning A relatively small number of milestones and local paths are sufficient to capture the connectivity of the free space. Visibility properties of free space  Notion of expansive free space (2 nd paper)

10 Issues  Why random sampling? Convenient incremental scheme  Smart sampling strategies Topic for next two classes  Final path smoothing


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