Environment Recognition for Path Generation in Autonomous Mobile Robots

Ulises Orozco-Rosas, Kenia Picos, Oscar Montiel, Oscar Castillo

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

An efficient algorithm for path generation in autonomous mobile robots using a visual recognition approach is presented. The proposal includes image filtering techniques by employing an inspecting camera to sense a cluttered environment. Template matching filters are used to detect several environment elements, such as obstacles, feasible terrain, the target location, and the mobile robot. The proposed algorithm includes the parallel evolutionary artificial potential field to perform the path planning for autonomous navigation of the mobile robot. Our problem to be solved for autonomous navigation is to safely take a mobile robot from the starting point to the target point employing the path with the shortest distance and which also contains the safest route. To find the path that satisfies this condition, the proposed algorithm chooses the best candidate solution from a vast number of different paths calculated concurrently. For achieving efficient autonomous navigation, the proposal employs a parallel computation approach for the evolutionary artificial potential field algorithm for path generation and optimization. Experimental results yield accuracy in environment recognition in terms of quantitative metrics. The proposed algorithm demonstrates efficiency in path generation and optimization.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
PublisherSpringer
Pages273-288
Number of pages16
DOIs
StatePublished - 1 Jan 2020

Publication series

NameStudies in Computational Intelligence
Volume827
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503

Fingerprint

Mobile robots
Navigation
Template matching
Motion planning
Cameras

Keywords

  • Mobile robots
  • Object recognition
  • Parallel evolutionary artificial potential field
  • Path planning
  • Template matching

Cite this

Orozco-Rosas, U., Picos, K., Montiel, O., & Castillo, O. (2020). Environment Recognition for Path Generation in Autonomous Mobile Robots. In Studies in Computational Intelligence (pp. 273-288). (Studies in Computational Intelligence; Vol. 827). Springer. https://doi.org/10.1007/978-3-030-34135-0_19
Orozco-Rosas, Ulises ; Picos, Kenia ; Montiel, Oscar ; Castillo, Oscar. / Environment Recognition for Path Generation in Autonomous Mobile Robots. Studies in Computational Intelligence. Springer, 2020. pp. 273-288 (Studies in Computational Intelligence).
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Orozco-Rosas, U, Picos, K, Montiel, O & Castillo, O 2020, Environment Recognition for Path Generation in Autonomous Mobile Robots. in Studies in Computational Intelligence. Studies in Computational Intelligence, vol. 827, Springer, pp. 273-288. https://doi.org/10.1007/978-3-030-34135-0_19

Environment Recognition for Path Generation in Autonomous Mobile Robots. / Orozco-Rosas, Ulises; Picos, Kenia; Montiel, Oscar; Castillo, Oscar.

Studies in Computational Intelligence. Springer, 2020. p. 273-288 (Studies in Computational Intelligence; Vol. 827).

Research output: Chapter in Book/Report/Conference proceedingChapter

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Orozco-Rosas U, Picos K, Montiel O, Castillo O. Environment Recognition for Path Generation in Autonomous Mobile Robots. In Studies in Computational Intelligence. Springer. 2020. p. 273-288. (Studies in Computational Intelligence). https://doi.org/10.1007/978-3-030-34135-0_19