Research on Gas Source Location of Quadruped Robot Based on DDQN

被引：0

作者：

Li, Fengyun ^{[1
]}

Cheng, Lei ^{[1
]}

Wang, Wenle ^{[1
]}

Hou, Bingbing ^{[1
]}

机构：

[1] Wuhan Univ Sci & Technol, Coll Informat Sci & Engn, Wuhan 430080, Peoples R China

来源：

PROCEEDINGS OF 2023 CHINESE INTELLIGENT SYSTEMS CONFERENCE, VOL I | 2023年 / 1089卷

关键词：

Air source localization; DDQN; Quadruped robot; Reinforcement learning; ALGORITHMS;

D O I：

10.1007/978-981-99-6847-3_44

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This study proposes a solution for air source exploration using the Double DQN algorithm on a quadruped robot platform. Gas dispersion data-based environment and simulator were designed to train the olfactory quadruped robot by Fluent software and ROS. Quadruped robots, with their discrete foothold, multi-degree of freedom, and multi-limb characteristics, excel in complex road conditions. By utilizing the dual-value network ofDDQNalgorithm, the robot achieves accurate air source detection. Experimental results showthat the robot efficiently locates air sources even in scenes with obstacles. This method finds practical applications in rugged ground settings like pipe corridors and mine caves, addressing potential dangers to humans and organisms.

引用

页码：519 / 528

页数：10

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