POA: Passable Obstacles Aware Path-planning Algorithm for Navigation of a Two-wheeled Robot in Highly Cluttered Environments

Alexander Petrovsky, Yomna Youssef, Kirill Myasoedov, Artem Timoshenko, Vladimir Guneavoi +2 more
7/16/2023
cs.ROcs.AI

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Abstract

This paper focuses on Passable Obstacles Aware (POA) planner - a novel navigation method for two-wheeled robots in a highly cluttered environment. The navigation algorithm detects and classifies objects to distinguish two types of obstacles - passable and unpassable. Our algorithm allows two-wheeled robots to find a path through passable obstacles. Such a solution helps the robot working in areas inaccessible to standard path planners and find optimal trajectories in scenarios with a high number of objects in the robot's vicinity. The POA planner can be embedded into other planning algorithms and enables them to build a path through obstacles. Our method decreases path length and the total travel time to the final destination up to 43% and 39%, respectively, comparing to standard path planners such as GVD, A*, and RRT*

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Cite this paper

@article{petrovsky2023poa,
  title  = {POA: Passable Obstacles Aware Path-planning Algorithm for Navigation of a Two-wheeled Robot in Highly Cluttered Environments},
  author = {Alexander Petrovsky and Yomna Youssef and Kirill Myasoedov and Artem Timoshenko and Vladimir Guneavoi and Ivan Kalinov and Dzmitry Tsetserukou},
  year   = {2023},
  eprint = {2307.08141},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2307.08141v1}
}

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