JOURNAL ARTICLE

Dynamic cognitive maps for robot route planning in complex workplaces represented by abstract mazes.

  • Published In: Concurrency & Computation: Practice & Experience, 2023, v. 35, n. 1. P. 1 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: Huang, Ying; Li, Wei 3 of 3

Abstract

Adaptive path planning and optimization for robots are a persistent challenge due to the lack of a cognitive map of the complex and dynamic environments. This paper presents a cognitive‐map‐based method for dynamic robot path planning by a formal maze model for workplace layouts representation. The maze model and global path trees provide a cognitive map for the robot to aware the environment. A theory of dynamic Paths Finding and Optimization (PFO) is developed. Powered by the PFO algorithm, a robot is able to autonomously explore the optimal path in a complex workplace by a single sight‐read of its layout. The maze based PFO methodology provides robot for an efficient real time path cognition and optimization algorithm for dealing with dynamic workplaces. A set of experiments demonstrates the efficiency of the method, which extends traditional stepwise robot vision technologies to cognitive‐map‐driven global path optimization. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Concurrency & Computation: Practice & Experience. 2023/01, Vol. 35, Issue 1, p1
  • Document Type:Article
  • Subject Area:Psychology
  • Publication Date:2023
  • ISSN:15320626
  • DOI:10.1002/cpe.7426
  • Accession Number:160717381
  • Copyright Statement:Copyright of Concurrency & Computation: Practice & Experience is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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