Robotics: Science and Systems XVII

Sampling-Based Motion Planning on Sequenced Manifolds

Peter Englert, Isabel M Rayas Fernández, Ragesh Kumar Ramachandran, Gaurav Sukhatme

Abstract:

We address the problem of planning robot motions in constrained configuration spaces where the constraints change throughout the motion. The problem is formulated as a fixed sequence of intersecting manifolds; which the robot needs to traverse in order to solve the task. We specify a class of sequential motion planning problems that fulfill a particular property of the change in the free configuration space when transitioning between manifolds. For this problem class; the algorithm Planning on Sequenced Manifolds (PSM*) is developed which searches for optimal intersection points between manifolds by using RRT* in an inner loop with a novel steering strategy. We provide a theoretical analysis regarding PSM*s probabilistic completeness and asymptotic optimality. Further; we evaluate its planning performance on multi-robot object transportation tasks.

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Bibtex:

  
@INPROCEEDINGS{Englert-RSS-21, 
    AUTHOR    = {Peter Englert AND Isabel M {Rayas Fernández} AND Ragesh Kumar Ramachandran AND Gaurav Sukhatme}, 
    TITLE     = {{Sampling-Based Motion Planning on Sequenced Manifolds}}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2021}, 
    ADDRESS   = {Virtual}, 
    MONTH     = {July}, 
    DOI       = {10.15607/RSS.2021.XVII.039} 
}