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Growing neural gas based navigation system in unknown terrain environment for an autonomous mobile robot

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Abstract

Recently, various types of autonomous robots have been expected in many fields such as a disaster site, forest, and so on. The autonomous robots are assumed to be utilized in unknown environments. In such environments, a path planning to a target point set in the unknown area is a fundamental capability for efficiently executing tasks. To realize the 3D space perception, GNG with Different Topologies (GNG-DT) proposed in our previous work can learn the multiple topological structures with in the framework of learning algorithm. This paper proposes a GNG-DT based 3D perception method by utilizing the multiple topological structures for perceiving the 3D unknown terrain environment and a path planning method to the target point set in the unknown area. Especially, a traversability property of the robot is added to GNG-DT as a new property of the topological structures for clustering the 3D terrain environment from the 3D point cloud measured by 3D Lidar. Furthermore, this paper proposes a path planning method utilizing the multiple topological structures. Next, this paper shows several experimental results of the proposed method using simulation terrain environments for verifying the effectiveness of our proposed method. Finally, we summarize our proposed method and discuss the future direction on this research.

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Data availability

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

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Acknowledgements

This work was supported by Wesco Scientific Promotion Foundation and JSPS KAKENHI Grant number 20K19894.

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Authors and Affiliations

  1. Graduate school of natural science and technology, Okayama University, Okayama, Japan

    Yuichiro Toda, Koki Ozasa & Takayuki Matsuno

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  1. Yuichiro Toda
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  2. Koki Ozasa
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  3. Takayuki Matsuno
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Correspondence to Yuichiro Toda.

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This work was submitted and accepted for the Journal Track of the joint symposium of the 28th International Symposium on Artificial Life and Robotics, the 8th International Symposium on BioComplexity, and the 6th International Symposium on Swarm Behavior and Bio-Inspired Robotics (Beppu, Oita, January 25–27, 2023).

Yuichiro Toda is the presenter of this paper.

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Toda, Y., Ozasa, K. & Matsuno, T. Growing neural gas based navigation system in unknown terrain environment for an autonomous mobile robot. Artif Life Robotics 28, 76–88 (2023). https://doi.org/10.1007/s10015-022-00826-y

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  • DOI: https://doi.org/10.1007/s10015-022-00826-y

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