Gait Parameter Optimization of Quadruped Robot Under Energy Consumption Index Based on Reinforcement Learning

被引：0
|
作者：
Chen, Lu [1 ]
Ma, Hongxu [1 ]
Lang, Lin [1 ,2 ]
Liu, Xiangming [1 ]
Wei, Qing [1 ]
An, Honglei [1 ]
机构：
[1] Natl Univ Def Technol, Coll Intelligence Sci & Technol, Changsha, Hunan, Peoples R China
[2] Hunan Univ Finance & Econ, Changsha, Hunan, Peoples R China
来源：
2022 INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS AND MECHATRONICS (ICARM 2022) | 2022年
基金：
美国国家科学基金会;
关键词：
D O I：
10.1109/ICARM54641.2022.9959165
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the gait optimization of quadruped bionic robot is studied under the unified energy consumption index. Firstly, an energy consumption index of quadruped robot is established. Secondly, the reinforcement learning method is used to optimize the gait parameters of the quadruped robot, so that the quadruped robot can gradually find the gait parameter combination with the lowest energy consumption in the current state in the interaction with the environment. In order to verify the effectiveness of this method, this paper completes the optimization of gait parameters combined with MIT cheetah software and DDQN network.
引用
收藏
页码：972 / 977
页数：6
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