Graduated Fidelity Motion Planning
Mihail Pivtoraiko and Alonzo Kelly. Graduated Fidelity Motion Planning. In Proceedings of the International Symposium on Combinatorial Search, 2011.
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Abstract
This paper presents an approach to differentially constrained robot motion planning and efficient replanning. Satisfaction of differential constraints is guaranteed by the search space which consists of motions that satisfy the constraints by construction. Any systematic replanning algorithm, e.g. D*, can be utilized to search the state lattice to find a motion plan that satisfies the differential constraints, and to repair it efficiently in the event of a change in the environment. Further efficiency is obtained by varying the fidelity of representation of the planning problem. High fidelity is utilized where it matters most, while it is lowered in the areas that do not affect the quality of the plan significantly. The paper presents a method of modifying the fidelity between replans, thereby enabling dynamic flexibility of the search space, while maintaining its compatibility with replanning algorithms. The approach is especially suited for mobile robotics applications in unknown challenging environments. We successfully applied the motion planner on a real robot: the planner featured 10Hz replan rate on minimal computing hardware [2], while satisfying the car-like differential constraints.
BibTeX
@INPROCEEDINGS{pivtoraiko_kelly_socs11,
author = {Mihail Pivtoraiko and Alonzo Kelly},
title = {Graduated Fidelity Motion Planning},
booktitle = {Proceedings of the International Symposium on Combinatorial Search},
year = {2011},
abstract = { This paper presents an approach to differentially
constrained robot motion planning and efficient
replanning. Satisfaction of differential constraints
is guaranteed by the search space which consists of
motions that satisfy the constraints by
construction. Any systematic replanning algorithm,
e.g. D*, can be utilized to search the state lattice
to find a motion plan that satisfies the
differential constraints, and to repair it
efficiently in the event of a change in the
environment. Further efficiency is obtained by
varying the fidelity of representation of the
planning problem. High fidelity is utilized where it
matters most, while it is lowered in the areas that
do not affect the quality of the plan
significantly. The paper presents a method of
modifying the fidelity between replans, thereby
enabling dynamic flexibility of the search space,
while maintaining its compatibility with replanning
algorithms. The approach is especially suited for
mobile robotics applications in unknown challenging
environments. We successfully applied the motion
planner on a real robot: the planner featured 10Hz
replan rate on minimal computing hardware [2], while
satisfying the car-like differential constraints. },
bib2html_pubtype = {Refereed Conference Papers},
bib2html_rescat = {Kinodynamic Planning}
}