Design And Implementation Of Balanced Optimal Grasping Algorithm For Multi-manipulator

With the proposal of the industrial internet,intelligent manufacturing and other concepts and the continuous promotion of "Made in China 2025",China’s manufacturing industry is in a critical period of strategic transformation.As an important supporting equipment,industrial manipulator has received increasingly extensive attention.At present,the research of manipulator system involves two key problems: end-effector trajectory tracking and multimanipulator task allocation.Therefore,it is of great significance to study how to improve the trajectory tracking control performance of the manipulator and allocate tasks reasonably.In order to solve the above problems,this paper takes the grasping system composed of a single camera and several manipulators on the conveyor belt as the research object.An effective control method is proposed for the end-effector trajectory tracking of the manipulator,and the balanced task allocation of the multi-manipulator is also studied.The main research work and achievements are as follows:(1)The kinematics and workspace of the parallel manipulator are analyzed.The structure of the parallel manipulator is simplified to obtain its geometric model,and the coordinate system is established.Then the forward and inverse kinematics analysis and solution of the parallel manipulator are carried out,and the correctness of the analysis method is verified by MATLAB.On the basis of kinematics analysis,the reachable workspace of manipulator is obtained by Monte Carlo method,and the desired workspace of manipulator is designed and solved.(2)For the trajectory tracking control problem of the manipulator end-effector,a fast and high precision control algorithm is designed.The Lagrange method is used to establish the dynamics model of the manipulator.Considering the influence of model uncertainty,friction,disturbances and other factors,an integral sliding mode robust control algorithm based on HJI(Hamilton-Jacobi Inequality)theory and nonlinear disturbance observer is proposed.The simulation results show that compared with the approach law based sliding mode control algorithm and disturbance observer based sliding mode control algorithm,this algorithm has better control performance,which can effectively improve the transient response,reduce the steady-state error and weaken chattering.(3)To solve the problem of multi-manipulator task allocation,a balanced task allocation algorithm is designed and the operating parameters of the system are optimized.In this paper,a balanced task allocation strategy based on improved genetic algorithm is proposed.This strategy can balance the load difference between manipulators while ensuring the system does not miss grasp,and achieve equal life operation to the maximum extent.In order to give full play to the performance of the manipulator and reduce the waiting time,the improved particle swarm optimization algorithm is used to optimize the operating parameters of the system and further improve the comprehensive grasping rate.Simulation results show that the proposed algorithm is balanced and effective.(4)Build a multi-manipulator grasping platform and conduct simulation verification.In Coppelia Sim,a grasping system which including conveyor belt,camera and several manipulators is built.The program of task allocation algorithm is written and embedded in the software,and the feasibility of the balanced allocation algorithm is verified by the experimental results of different allocation algorithms.