Path planning algorithm using the values clustered by k-means

Won Seok Kang, Seung Hyun Lee, Berdakh Abibullaev, Jin Wook Kim, Jinung An

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Path planning has been studied focusing on finding the shortest paths or smallest movements. The previous methods, however, are not suitable for stable movements on real environments in which various dynamic obstacles exist. In this paper, we suggest a path planning algorithm that makes the movement of an autonomous robot easier in a dynamic environment. Our focus is based on finding optimal movements for mobile robot to keep going on a stable situation but not on finding shortest paths or smallest movements. The proposed algorithm is based on GA and uses kmeans cluster analysis algorithm to recognize the much more information of obstacles distribution in real-life space. Simulation results confirmed to have better performance and stability of the proposed algorithm. In order to validate our results, we compared with a previous algorithm based on grid maps-based algorithm for static obstacles and dynamic obstacles environment.

Original languageEnglish
Title of host publicationProceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10
Pages959-962
Number of pages4
Publication statusPublished - 2010
Externally publishedYes
Event15th International Symposium on Artificial Life and Robotics, AROB '10 - Beppu, Oita, Japan
Duration: Feb 4 2010Feb 6 2010

Other

Other15th International Symposium on Artificial Life and Robotics, AROB '10
CountryJapan
CityBeppu, Oita
Period2/4/102/6/10

Fingerprint

Motion planning
Cluster analysis
Mobile robots
Robots

Keywords

  • Clustering and static/dynamic obstacles
  • GA
  • Path Planning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

Cite this

Kang, W. S., Lee, S. H., Abibullaev, B., Kim, J. W., & An, J. (2010). Path planning algorithm using the values clustered by k-means. In Proceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10 (pp. 959-962)

Path planning algorithm using the values clustered by k-means. / Kang, Won Seok; Lee, Seung Hyun; Abibullaev, Berdakh; Kim, Jin Wook; An, Jinung.

Proceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10. 2010. p. 959-962.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kang, WS, Lee, SH, Abibullaev, B, Kim, JW & An, J 2010, Path planning algorithm using the values clustered by k-means. in Proceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10. pp. 959-962, 15th International Symposium on Artificial Life and Robotics, AROB '10, Beppu, Oita, Japan, 2/4/10.
Kang WS, Lee SH, Abibullaev B, Kim JW, An J. Path planning algorithm using the values clustered by k-means. In Proceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10. 2010. p. 959-962
Kang, Won Seok ; Lee, Seung Hyun ; Abibullaev, Berdakh ; Kim, Jin Wook ; An, Jinung. / Path planning algorithm using the values clustered by k-means. Proceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10. 2010. pp. 959-962
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