Auto-splitting D* lite path planning for large disaster area

Shin nyeong Heo*, Jiaheng Chen, Yu chi Liao, Hee hyol Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This research introduces a new path planning method for rescue robots in a dynamic and partially known area when the robots are performing tasks in a large area. The path planning of the rescue robots that move in the dynamic area is introduced to solve the issue of unnecessary areas, which are the disadvantages of the existing D*-based algorithms. This paper proposes a method to eliminate unnecessary expanded nodes of the dynamic and partially known environment by segmenting a map with an auto-clustering algorithm, which is able to achieve a faster execution time than conventional algorithms. Furthermore, to show the effectiveness of the proposed algorithms, an expected value of re-planned nodes in the dynamic and partially known area is introduced using a probability-based approach.

Original languageEnglish
JournalIntelligent Service Robotics
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Auto-clustering algorithm
  • D*-based algorithm
  • Dynamic environment
  • Global path planning
  • Large-scale area
  • Partially known area

ASJC Scopus subject areas

  • Computational Mechanics
  • Engineering (miscellaneous)
  • Mechanical Engineering
  • Artificial Intelligence

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