Efficient Constrained Path Planning via Search in State Lattices

Mihail Pivtoraiko and Alonzo Kelly. Efficient Constrained Path Planning via Search in State Lattices. In Proceedings of the 8th International Symposium on Artificial Intelligence, Robotics and Automation in Space, 2005.

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Abstract

We propose a novel approach to constrained path planning that is based on a special search space which efficiently encodes feasible paths. The paths are encoded implicitly as connections between states, but only feasible and local connections are included. Once this search space is developed, we systematically generate a nearminimal set of spatially distinct path primitives. This set expresses the local connectivity of constrained motions and also eliminates redundancies. The set of primitives is used to define heuristic search, and thereby create a very efficient path planner at the chosen resolution. We also discuss a wide variety of space and terrestrial robotics applications where this motion planner can be especially useful.

BibTeX

@INPROCEEDINGS{pivtoraiko_kelly_isairas05,
  author = {Mihail Pivtoraiko and Alonzo Kelly},
  title = {Efficient Constrained Path Planning via Search in State Lattices},
  booktitle = {Proceedings of the 8th International Symposium on Artificial Intelligence,
	Robotics and Automation in Space},
  year = {2005},
  abstract = {We propose a novel approach to constrained path planning
                  that is based on a special search space which
                  efficiently encodes feasible paths. The paths are
                  encoded implicitly as connections between states,
                  but only feasible and local connections are
                  included. Once this search space is developed, we
                  systematically generate a nearminimal set of
                  spatially distinct path primitives. This set
                  expresses the local connectivity of constrained
                  motions and also eliminates redundancies. The set of
                  primitives is used to define heuristic search, and
                  thereby create a very efficient path planner at the
                  chosen resolution. We also discuss a wide variety of
                  space and terrestrial robotics applications where
                  this motion planner can be especially useful.},
  bib2html_pubtype = {Refereed Conference Papers},
  bib2html_rescat = {Kinodynamic Planning},
  owner = {mihail},
  timestamp = {2010.08.07}
}

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