Research On Industrial Robot Trajectory Planning Algorithm With Optimal Time And Energy

Nowadays,industrial robots can be seen everywhere in various industrial fields because of their advantages of high efficiency,energy saving and environmental protection.In the field of robot research,trajectory planning of industrial robot has always been a research hotspot.The purpose is to find a smooth,time-saving,energy-saving and low residual vibration joint curve between certain points under given constraints,so that the robot can complete different tasks with high performance.This paper studies the six DOF industrial robot in time and energy,and the main research contents are as follows:(1)The kinematics model of the robot is established by using the screw theory,and the forward and inverse solutions of the robot are verified.Compared with DH model,the kinematic model based on screw has obvious geometric significance,which simplifies the analysis of mechanical structure.When solving the inverse kinematics solution,it will not produce singular solution and has high reliability.(2)By improving the traditional cosine jerk function,the amount of motion of the robot can be kept in a saturated state for as long as possible,which greatly improves the operating efficiency of the robot between any two points in the workspace.When solving the four time parameters in the improved algorithm,the solution is refined into 8 cases.After the running time of each joint is obtained,the largest running time among the six joints is selected as the optimal time.The simulation results show that this method has better operating efficiency and lower mechanical residual vibration.(3)Taking the trajectory energy consumption of the palletizing robot as the research goal,a mathematical model of the palletizing robot moving back and forth between multiple points in the operating space is established based on the joint torque obtained by dynamics.Taking into account the constraints of a given operating cycle,kinematics and dynamics,an improved gravitational search algorithm is proposed to find the optimal trajectory of the energy consumption of the depalletizing robot.Aiming at the problem that the traditional gravitation search algorithm(GSA)balances the global search and the local search ability,the GSA is improved by improving the gravitation constant,adding the premature convergence judgment and adding the Gauss operator,and using the classic test function to test the performance of improved algorithm.Taking the ABB1410 robot as the research object,a simulation experiment was carried out on MATLAB.The results show that the energy consumption of the robot's trajectory is significantly reduced under the condition of satisfying the constraints.