Coordination control of dual-arm robot based on modeled predictive control

This paper presents a master-slave force hybrid coordinated motion control method which is based on the model predictive control (MPC) algorithm. In the paper, the kinematics model of the dual 6-DOF arms is build. Six axis force sensors are installed at the ends of the two arms, the master arm adopts the position control method and the based on the model predictive control algorithm DMC theory force/position hybrid control method is adopted in the slave arm. According to the kinematic model of the dual-arms, the end pose and joint angle rule conversion library is established, and the motion prediction model of the manipulator also is established. By using these models, the slave arm can acquire the position and direction of the master arm synchronously, and the current end position of the master arm is also used as the reference input value of the end position of the slave arm. The rotation operation sequence of the joint angle rule conversion library predicted model and end pose apply to the joint motor, drive the end of the robot arm to move to the target position. After doing these we could synchronously realize position tracking. In our experiment the current position tracking could be realized through the simulation analysis of six degree of freedom dual arm robot.