Research On Motion Planning And PID Control Strategy Of Palletizing Industrial Robot

With the vigorous promotion of "Industry 4.0" and "Made in China 2025",palletizing robots have been widely used in various automated manufacturing fields with their advantages of efficiency,precision and safety.At the same time,the working environment is becoming increasingly complex and the operational requirements are constantly increasing.Therefore,robot obstacle avoidance path planning and trajectory planning are urgent problems to be solved at present,which has extremely important practical significance.Taking IRB 1600 six-degree-of-freedom robot as the research object,this paper mainly conducts research from four aspects:obstacle avoidance path planning,multi-objective trajectory optimization based on time-energy-impact synthesis and joint control.The paper mainly completes the following:Firstly,aiming at the collision detection problem in the process of robot path planning,this paper uses cylindrical and spherical bounding boxes to simplify the robotic arm and obstacles.RRT-star algorithm and RRT-connect algorithm were selected in the same three-dimensional obstacle environment to carry out path planning experimental verification.The experimental results show that the path length searched by the RRT-connect algorithm is reduced by 10%compared with the path length searched by the RRT-star algorithm,and the average planning time is shortened by 69%,and the overall performance of the RRT-connect algorithm is better than that of the RRT-star algorithm.Secondly,this paper improves the standard whale optimization algorithm(WOA)from four aspects:tent mapping initializes the population,improves the nonlinear convergence factor,introduces the adaptive weight strategy,and improves the adaptive probability threshold.The improved whale optimization algorithm(IWOA)was used to carry out time-energy consumption-impact comprehensive optimization of the interpolation trajectories of the five NURBS curves,and the normalization function was used to obtain the optimal solution of the selected Pareto.Compared with the optimized trajectory,the efficiency of the optimized trajectory is increased by 24%,the energy consumption is reduced by 23%,and the impact is reduced by 31%.Finally,the parts of the 3D model of the robotic arm are imported into Solid Works software,assembled according to the D-H parameters of the robotic arm,and the coordinate system and initial attitude are assigned to the corresponding linkage.The generated URDF file is added to Simulink,and the PID control algorithm is used to visually simulate the robotic arm.The simulation results show that the overall performance of the PID control algorithm is good,and and the trajectory tracking error fluctuates within the effective range,which further proves the effectiveness of the improved whale optimization algorithm.