Adaptive Anytime Motion Planning for Robust Robot Navigation in Natural Environments

Mihail Pivtoraiko. Adaptive Anytime Motion Planning for Robust Robot Navigation in Natural Environments. In AT-EQUAL '09: Proceedings of the 2009 Advanced Technologies for Enhanced Quality of Life, pp. 123–129, 2009.
Homayoun Seraji best paper award

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Abstract

The problem of robot navigation is treated under constraints of limited perception horizon in complex, cluttered, natural environments. We propose a solution based on our previous work in fast constrained motion planning, where arbitrary mobility constraints could be satisfied while the planning problem is reduced to unconstrained heuristic search in state lattices. By trading off optimality, we improve planner run-times and increase robustness through achieving anytime planning quality, such that it becomes possible to integrate the planner within the high speed navigation framework. We show that using a planner in navigation works well and fast enough for real vehicle implementation, while it presents a number of important benefits over state-of-the-art in navigation.

BibTeX

@INPROCEEDINGS{pivtoraiko_atequal09,
  author = {Mihail Pivtoraiko},
  title = {Adaptive Anytime Motion Planning for Robust Robot Navigation in Natural
	Environments},
  booktitle = {AT-EQUAL '09: Proceedings of the 2009 Advanced Technologies for Enhanced
	Quality of Life},
  year = {2009},
  pages = {123--129},
  abstract = {The problem of robot navigation is treated under
                  constraints of limited perception horizon in
                  complex, cluttered, natural environments. We propose
                  a solution based on our previous work in fast
                  constrained motion planning, where arbitrary
                  mobility constraints could be satisfied while the
                  planning problem is reduced to unconstrained
                  heuristic search in state lattices. By trading off
                  optimality, we improve planner run-times and
                  increase robustness through achieving anytime
                  planning quality, such that it becomes possible to
                  integrate the planner within the high speed
                  navigation framework. We show that using a planner
                  in navigation works well and fast enough for real
                  vehicle implementation, while it presents a number
                  of important benefits over state-of-the-art in
                  navigation.},
  bib2html_pubtype = {Refereed Conference Papers},
  bib2html_rescat = {Robot Navigation},
  wwwnote =	 {<i>Homayoun Seraji</i> best paper award},
  doi = {10.1109/AT-EQUAL.2009.33},
  isbn = {978-0-7695-3753-5}
}

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