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ORIGINAL RESEARCH article

Front. Robot. AI
Sec. Robot Learning and Evolution
Volume 11 - 2024 | doi: 10.3389/frobt.2024.1388634

Tangle-and Contact-free Path Planning for a Tethered Mobile Robot using Deep Reinforcement Learning

Provisionally accepted
Ryuki Shimada Ryuki Shimada *Genya Ishigami Genya Ishigami
  • Faculty of Science and Technology, Keio University, Yokohama, Japan

The final, formatted version of the article will be published soon.

    This paper presents a tangle-and contact-free path planning (TCFPP) for a mobile robot attached to a base station with a finite-length cable. This type of robot, called a tethered mobile robot, can endure long-time exploration with a continuous power supply and stable communication via its cable. However, the robot faces potential hazards that endanger its operation such as cable snagging on and cable entanglement with obstacles and the robot. To address these challenges, our approach incorporates homotopy-aware path planning into deep reinforcement learning. The proposed reward design in the learning problem penalizes the cable-obstacle and cable-robot contacts and encourages the robot to follow the homotopy-aware path toward a goal. We consider two distinct scenarios for the initial cable configuration: 1) the robot pulls the cable sequentially from the base while heading for the goal, and 2) the robot moves to the goal starting from a state where the cable has already been partially deployed. The proposed method is compared with naive approaches in terms of contact avoidance and path similarity. Simulation results revealed that the robot can successfully find a contact-minimized path under the guidance of the reference path in both scenarios.

    Keywords: Tethered mobile robot, path planning, Homotopy class, reinforcement learning, Deep Q-network

    Received: 20 Feb 2024; Accepted: 24 Jul 2024.

    Copyright: © 2024 Shimada and Ishigami. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Ryuki Shimada, Faculty of Science and Technology, Keio University, Yokohama, Japan

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.