公开(公告)号：US20240351199A1

公开(公告)日：2024-10-24

申请号：US18739773

申请日：2024-06-11

Applicant: ZHENGZHOU UNIVERSITY OF LIGHT INDUSTRY

Inventor： Hao LI ,  Gen LIU ,  Yonglei WU ,  Haoqi WANG ,  Linli LI ,  Xiaoyu WEN ,  Shizhong WEI ,  Yuyan ZHANG ,  Like ZHANG ,  Weifei GUO

IPC: B25J9/16

CPC classification number: B25J9/163 ,  B25J9/1661

Abstract: A method for intelligently controlling a mechanical arm includes building a twin model of a mechanical arm, and extracting a state parameter and an action parameter corresponding to task characteristics from the twin model; determining a reward function corresponding to the task characteristics; training a twin delayed deep deterministic policy gradient (TD3) reinforcement learning model; simulating in the twin model based on a physical state parameter of the mechanical arm by using the TD3 reinforcement learning model, to obtain a controllable parameter; and controlling the mechanical arm to execute a corresponding task by using the controllable parameter. The TD3 reinforcement learning model is built based on the state parameter and the action parameter corresponding to the task characteristics and the reward function corresponding to the task characteristics, which can adapt to a dynamically changing environment and requirements for multiple tasks.