Research And Implementation Of Coordinated Control Of Six-degree-of-freedom Dual Manipulator

As the darling in the field of artificial intelligence,dual-manipulator provides convenience for our lives and industrial production all the time,and has also made great contributions to the development of science and technology and social progress.This paper takes the dualmanipulator system composed of two six-degree-of-freedom manipulators as the research object,and studies the collision avoidance path planning and coordinated control algorithm during the operation of the dual-manipulator system.Firstly,the dual-manipulator system model is built,the D-H parameter method is selected to establish the kinematics model of the manipulator,and the Lagrange method is selected to establish the dynamics model.According to the different task modes of dual-manipulator coordinated operation,the kinematic constraints of loose coordination and tight coordination are analyzed,and the internal/external force decomposition of the end contact force of the manipulator is realized.Secondly,according to the established model and the task requirements of dualmanipulator coordinated operation,the collision detection and collision avoidance path planning in the dual-manipulator system are studied.For the problem of collision avoidance path planning in the system,an improved APF-RRT fusion algorithm is proposed,and the improved APF is used to plan the path of the master/slave manipulator,The improved RRT is used to adaptively select the temporary target point to solve the problem of falling into local minimum in slave manipulator path planning.Simulation results show that the improved APFRRT fusion algorithm can solve the collision avoidance path planning problem of dualmanipulator system more quickly and accurately than the traditional algorithm.Aiming at the force/position hybrid control problem in the coordinated control of dualmanipulator,an impedance control algorithm integrating internal and external double loops is proposed.In order to solve the problem of poor adaptive performance when the manipulator interacts with the environment,a variable stiffness parameter adaptive impedance control scheme based on fuzzy neural network is proposed.Simulation results show that the proposed scheme has better advantages in position error and force tracking accuracy than the traditional position control scheme.Finally,a dual-manipulator experimental platform was built,and the feasibility of the algorithm proposed in this article was verified through experiments.