Search Methods in Motion Planning for Mobile Robots

Laura Paulino, Correy Hannum, Aparna S. Varde, Christopher J. Conti

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Mobile robots are used in a variety of applications ranging from domestic robotics to autonomous vehicles. In several applications, it is important to conduct motion planning for robots to find optimal paths with respect to parameters such as space and time. Classical search methods in the literature can be adapted to guide robotic paths and plan the motion of mobile robots. In this work, we explore three methods, namely the deterministic depth-first search and breadth-first search, and the heuristic A* search. We adapt these to the context of mobile robots navigating a maze and accordingly present the deployed algorithms and corresponding experiments with comparisons. These findings are useful in applications where mobile robots are utilized since the optimization of their paths is beneficial in motion planning. We explain applications of this study in areas such as human-robot collaboration (HRC) and unmanned aerial vehicles (UAVs) for motion planning in robotic paths.

Original languageEnglish
Title of host publicationIntelligent Systems and Applications - Proceedings of the 2021 Intelligent Systems Conference, IntelliSys
EditorsKohei Arai
PublisherSpringer Science and Business Media Deutschland GmbH
Pages802-822
Number of pages21
ISBN (Print)9783030821982
DOIs
StatePublished - 2022
Event Intelligent Systems Conference, IntelliSys 2021 - Virtual, Online
Duration: 2 Sep 20213 Sep 2021

Publication series

NameLecture Notes in Networks and Systems
Volume296
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference Intelligent Systems Conference, IntelliSys 2021
CityVirtual, Online
Period2/09/213/09/21

Keywords

  • A* search
  • Breadth-first search
  • Depth-first search
  • Mobile robots
  • Motion planning
  • Robot path optimization

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