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Autonomous Wheeled Locomotion on Irregular Terrain with Tactile Sensing

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Robotics in Natural Settings (CLAWAR 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 530))

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Abstract

Adopting the concept of the tactile wheel, which considers the interaction between the wheel and the ground, this paper simulates reinforcement learning to show the usefulness of tactile sensing for autonomous wheeled robots on irregular terrain and to clarify the characteristics of the information to be acquired. A wheeled robot model with a wheel-on-leg structure is created and tested on two types of irregular terrain. The tactile information from each wheel is used as part of the reinforcement learning state. The average return and sample efficiency respectively increase by factors of 1.18 and 2.21 on uneven terrain. On fractal terrain, they increase by factors of 1.31 and 2.51 times, respectively, confirming the usefulness of tactile information. Tactile wheels using analog tactile information perform better in terms of adaptability to unknown terrain.

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Acknowledgements

This work was supported by JSPS KAKENHI Grant Number 18H05466.

Author information

Authors and Affiliations

  1. Graduate School of Information Science and Technology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan

    Hiroki Tomioka, Masahiro Ikeda, Keung Or, Ryuma Niiyama & Yasuo Kuniyoshi

  2. School of Science and Technology, Meiji University, 1-1-1 Higashimita, Tama-ku, Kanagawa, Japan

    Masahiro Ikeda, Keung Or & Ryuma Niiyama

Authors
  1. Hiroki Tomioka
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  2. Masahiro Ikeda
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  3. Keung Or
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  4. Ryuma Niiyama
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  5. Yasuo Kuniyoshi
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Corresponding author

Correspondence to Hiroki Tomioka .

Editor information

Editors and Affiliations

  1. Faculty of Sciences and Technology, University of the Azores, Ponta Delgada, Portugal

    José M. Cascalho

  2. School of Engineering, London South Bank University, London, UK

    Mohammad Osman Tokhi

  3. School of Engineering, Polytechnic Institute of Porto, Porto, Portugal

    Manuel F. Silva

  4. Faculty of Sciences and Technology, University of the Azores, Ponta Delgada, Portugal

    Armando Mendes

  5. Mechanical, Materials and Manufacturing Engineering (M3), Faculty of Engineering, University of Nottingham, Nottingham, UK

    Khaled Goher

  6. Faculty of Sciences and Technology, University of the Azores, Ponta Delgada, Portugal

    Matthias Funk

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Tomioka, H., Ikeda, M., Or, K., Niiyama, R., Kuniyoshi, Y. (2023). Autonomous Wheeled Locomotion on Irregular Terrain with Tactile Sensing. In: Cascalho, J.M., Tokhi, M.O., Silva, M.F., Mendes, A., Goher, K., Funk, M. (eds) Robotics in Natural Settings. CLAWAR 2022. Lecture Notes in Networks and Systems, vol 530. Springer, Cham. https://doi.org/10.1007/978-3-031-15226-9_13

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