Prioritized multi-agent path finding for differential drive robots

Methods for centralized planning of the collision-free trajectories for a fleet of mobile robots typically solve the discretized version of the problem and rely on numerous simplifying assumptions, e.g. moves of uniform duration, cardinal only translations, equal speed and size of the robots etc., thus the resultant plans can not always be directly executed by the real robotic systems. To mitigate this issue we suggest a set of modifications to the prominent prioritized planner - AA-SIPP(m) - aimed at lifting the most restrictive assumptions (syncronized translation only moves, equal size and speed of the robots) and at providing robustness to the solutions. We evaluate the suggested algorithm in simulation and on differential drive robots in typical lab environment (indoor polygon with external video-based navigation system). The results of the evaluation provide a clear evidence that the algorithm scales well to large number of robots (up to hundreds in simulation) and is able to produce solutions that are safely executed by the robots prone to imperfect trajectory following. The video of the experiments can be found at https://youtu.be/Fer_irn4BG0. © 2019 IEEE.

Авторы
Yakovlev K. 1 , Andreychuk A. 2 , Vorobyev V.3
Сборник материалов конференции
Издательство
Institute of Electrical and Electronics Engineers Inc.
Язык
Английский
Статус
Опубликовано
Номер
8870957
Год
2019
Организации
  • 1 Federal Research Center Computer Science and Control of Russian, Academy of Sciences, National Research University Higher School of Economics, Russian Federation
  • 2 Peoples' Friendship University of Russia, RUDN University, Russian Federation
  • 3 National Research Center, Kurchatov Institute, Russian Federation
Ключевые слова
Mobile robots; Multi agent systems; Navigation systems; Petroleum reservoir evaluation; Collision-free trajectory; Differential drive robots; Equal sizes; Multi agent; Path finding; Robotic systems; Simplifying assumptions; Trajectory following; Robot programming
Дата создания
24.12.2019
Дата изменения
24.12.2019
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/55064/
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