Non-Communication Decentralized Multi-Robot Collision Avoidance in Grid Map Workspace with Double Deep Q-Network
1
Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400700, China
2
School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally.
Sensors 2021, 21(3), 841; https://doi.org/10.3390/s21030841
Received: 13 November 2020
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Revised: 27 December 2020
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Accepted: 29 December 2020
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Published: 27 January 2021
(This article belongs to the Special Issue Intelligent Sensors and Machine Learning)
This paper presents a novel decentralized multi-robot collision avoidance method with deep reinforcement learning, which is not only suitable for the large-scale grid map workspace multi-robot system, but also directly processes Lidar signals instead of communicating between the robots. According to the particularity of the workspace, we handcrafted a reward function, which considers both the collision avoidance among the robots and as little as possible change of direction of the robots during driving. Using Double Deep Q-Network (DDQN), the policy was trained in the simulation grid map workspace. By designing experiments, we demonstrated that the learned policy can guide the robot well to effectively travel from the initial position to the goal position in the grid map workspace and to avoid collisions with others while driving.
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MDPI and ACS Style
Chen, L.; Zhao, Y.; Zhao, H.; Zheng, B. Non-Communication Decentralized Multi-Robot Collision Avoidance in Grid Map Workspace with Double Deep Q-Network. Sensors 2021, 21, 841. https://doi.org/10.3390/s21030841
AMA Style
Chen L, Zhao Y, Zhao H, Zheng B. Non-Communication Decentralized Multi-Robot Collision Avoidance in Grid Map Workspace with Double Deep Q-Network. Sensors. 2021; 21(3):841. https://doi.org/10.3390/s21030841
Chicago/Turabian StyleChen, Lin, Yongting Zhao, Huanjun Zhao, and Bin Zheng. 2021. "Non-Communication Decentralized Multi-Robot Collision Avoidance in Grid Map Workspace with Double Deep Q-Network" Sensors 21, no. 3: 841. https://doi.org/10.3390/s21030841
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