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Path planning algorithm using the values clustered by k-means

Title
Path planning algorithm using the values clustered by k-means
Authors
Kang, W.-S.Lee, S.-H.Abibullaev, B.Kim, JAn, J.
DGIST Authors
Kang, W.-S.; Abibullaev, B.; Kim, J; An, J.
Issue Date
2010
Citation
15th International Symposium on Artificial Life and Robotics, AROB '10, 959-962
Type
Conference
Article Type
Conference Paper
ISBN
9784990288044
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. © 2010 ISAROB.
URI
http://hdl.handle.net/20.500.11750/3964
Publisher
Springer Japan
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Collection:
ETC2. Conference Papers
Information and Communication EngineeringInfoLab2. Conference Papers
Division of IoT∙Robotics Convergence Research2. Conference Papers


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