Artificial coordinating field and its application to motion planning of robots in uncertain dynamic environments

Xingjian Jing, Yuechao Wang, Dalong Tan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

11 Citations (Scopus)

Abstract

Artificial coordinating fields (ACF) are proposed to deal with the motion planning problems of mobile robots in uncertain dynamic environments. An ACF around an obstacle can generate two orthogonal force vectors to a robot: one is called the coordinating force vector which is purposively designed in this paper, and the other is the repulsive force vector which is the same as that in a conventional artificial potential field. The ACF is designed according to the updated motion purpose and the relative states of the robot with respect to its local environment, and it also satisfies the robot's dynamic constraints. The direction of the coordinating force can be determined on line according to an optimal evaluation function. The ACF can effectively remove the local minima, and reduce the oscillation of the planned trajectory between multiple obstacles. Only local knowledge of the environments is needed in the ACF-based motion planning. The properties of the ACF such as controllability, adaptability, safety and reachability are studied and discussed in detail in this paper. Theoretical analysis and simulations are given to illustrate our main results.
Original languageEnglish
Pages (from-to)577-594
Number of pages18
JournalScience in China, Series E: Technological Sciences
Volume47
Issue number5
DOIs
Publication statusPublished - 1 Oct 2004
Externally publishedYes

Keywords

  • Artificial coordinating fields
  • Artificial potential fields
  • Mobile robots
  • Motion planning
  • Uncertain dynamic environments

ASJC Scopus subject areas

  • Materials Science(all)
  • Engineering(all)

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