Fast and Feasible Deliberative Motion Planner for Dynamic Environments

Mihail Pivtoraiko and Alonzo Kelly. Fast and Feasible Deliberative Motion Planner for Dynamic Environments. In Workshop on Planning in Dynamic Environments at the International Conference on Robotics and Automation, 2009.

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Abstract

We present an approach to the problem of differentially constrained mobile robot motion planning in arbitrary time-varying cost fields. We construct a special search space which is ideally suited to the requirements of dynamic environments including a) feasible motion plans that satisfy differential constraints, b) efficient plan repair at high update rates, and c) deliberative goal-directed behavior on scales well beyond the effective range of perception sensors. The search space contains edges which adapt to the state sampling resolution yet aquire states exactly in order to permit the use of the dynamic programming principle without introducing infeasibility. It is a symmetric lattice based on a repeating unit of controls which permits off-line computation of the planner heuristic, motion simulation, and the swept volumes associated with each motion. For added planning efficiency, the search space features fine resolution near the vehicle and reduced resolution far away. Furthermore, its topology is updated in real-time as the vehicle moves in such a way that the underlying motion planner processes changing topology as an equivalent change in the dynamic environment. The planner was originally developed to cope with the reduced computation available on the Mars rovers. Experimental results with research prototype rovers demonstrate that the planner allows us to exploit the entire envelope of vehicle maneuverability in rough terrain, while featuring real-time performance.

BibTeX

@INCOLLECTION{pivtoraiko_kelly_icra09,
  author = {Mihail Pivtoraiko and Alonzo Kelly},
  title = {Fast and Feasible Deliberative Motion Planner for Dynamic Environments},
  booktitle = {Workshop on Planning in Dynamic Environments at the International Conference on Robotics and Automation},
  year = {2009},
  abstract = {We present an approach to the problem of differentially
                  constrained mobile robot motion planning in
                  arbitrary time-varying cost fields. We construct a
                  special search space which is ideally suited to the
                  requirements of dynamic environments including a)
                  feasible motion plans that satisfy differential
                  constraints, b) efficient plan repair at high update
                  rates, and c) deliberative goal-directed behavior on
                  scales well beyond the effective range of perception
                  sensors. The search space contains edges which adapt
                  to the state sampling resolution yet aquire states
                  exactly in order to permit the use of the dynamic
                  programming principle without introducing
                  infeasibility. It is a symmetric lattice based on a
                  repeating unit of controls which permits off-line
                  computation of the planner heuristic, motion
                  simulation, and the swept volumes associated with
                  each motion.  For added planning efficiency, the
                  search space features fine resolution near the
                  vehicle and reduced resolution far away.
                  Furthermore, its topology is updated in real-time as
                  the vehicle moves in such a way that the underlying
                  motion planner processes changing topology as an
                  equivalent change in the dynamic environment. The
                  planner was originally developed to cope with the
                  reduced computation available on the Mars
                  rovers. Experimental results with research prototype
                  rovers demonstrate that the planner allows us to
                  exploit the entire envelope of vehicle
                  maneuverability in rough terrain, while featuring
                  real-time performance.},
  bib2html_pubtype = {Workshop Papers},
  bib2html_rescat = {Kinodynamic Planning},
  owner = {mihail},
  timestamp = {2010.08.07}
}

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