Research On Stability Control Method Of Humanoid Robot Double-Arm Cart Pushing

In recent years,with the continuous progress of sensors and artificial intelligence technology,robots have begun to enter people's lives and provide services for human beings.Humanoid robots are easy to be accepted psychologically and live in harmony with human beings because of their similar shape and action characteristics.On the other hand,humanoid robots can work in the daily life environment like human beings without changing the life tools originally designed for human beings,so they have broad application prospects.In the service provided by humanoid robots,mobile manipulation,which can accurately identify the target,walk steadily with both feet and cooperate with two arms,is an important type of operation.It involves many key issues such as computer vision,biped stability control and force interaction control of humanoid robots.Humanoid robots have attracted wide attention at home and abroad.In this paper,the stability control method of humanoid robot double-arm pusher is studied.Firstly,a monocular vision ranging method based on piecewise fitting is proposed to recognize and locate indoor objects accurately.Secondly,the research on the compliance control method of double-arm pushing operation is carried out.By detecting the information of eight force sensors at the bottom of both feet of the humanoid robot,the whole body force and position of the robot pushing are perceived.Attitude changes,and the flexible control of the two arms,legs and the whole body is realized,which is verified by experiments.Thirdly,the task planning and control methods of the whole body mobile operation of humanoid robot are studied,and the cart operation experiments are carried out for different loads.Finally,the comprehensive experiments of the cart operation are carried out using the NAO platform of humanoid robot to verify the purpose of the research.Effectiveness of label positioning,double arm compliance control and stability control of mobile operation.The experimental results show that the humanoid robot can achieve better indoor environmental target recognition and approaching grasp,interactive flexible output control of double arm force and whole body stability control of heavy load mobile operation,and can achieve the goal of driving its own body weight about 6.7 times.