| In the face of the manufacturing industry's demand for upgrading industrial production efficiency,industrial robotic arms play an indispensable role in automated production.They are a key element for machine replacement,improving production efficiency,and reducing product costs.Especially in terms of improving production efficiency,higher requirements are put forward on the moving speed of the manipulator,so it is of great practical significance to study the path planning algorithm of the manipulator based on time priority.This paper takes the six-axis manipulator as the prototype of the research object,with the goal of reducing the movement time of the manipulator,and proposes a trajectory planning algorithm based on the LM algorithm;for the obstacle avoidance requirements during the movement of the manipulator,an improvement based on the LM algorithm is proposed.An obstacle avoidance path planning algorithm for a six-axis manipulator based on the artificial potential field method.The main content of this article is as follows:(1)Taking the six-axis manipulator as the prototype,according to the DH theory,the D-H coordinate system is established for the initial state of the manipulator,and the forward and inverse kinematics equations are deduced,thereby establishing the kinematics mathematical model.The whole process of inverse kinematics of the manipulator is deduced in detail,and a three-dimensional model of the manipulator is established using the MATLAB platform and Monte Carlo method,and the motion space range of the manipulator is simulated through experimental simulation.(2)On the premise of ensuring that the trajectory is continuous and not falling into the local optimal solution,with the goal of accelerating the iteration speed and reducing the trajectory planning and solving time,a trajectory planning algorithm for a six-axis manipulator based on the LM algorithm is proposed.The algorithm is based on the inverse Kinematics obtains the position of the joint angle sequence,and accelerates the iterative process of the algorithm by introducing the damping factor ? and convergence judgment conditions.When ? is large,the convergence speed approaches the gradient descent method,and when ? is small,the convergence speed approaches Gauss Newton law.While solving the relevant trajectories,it ensures that the joint angular velocity and acceleration curves are smooth.Experimental simulations show that this algorithm can not only obtain a relatively stable motion curve,but its iterative speed is better than other optimization algorithms in fitting discrete points.Fast iteration speed.(3)Since the manipulator needs to complete path planning to realize the needs of obstacle avoidance movement,this paper aims at the problem of the classical artificial potential field method being easy to fall into the local minimum,and adopts the idea based on the damping factor in the LM algorithm to improve the artificial potential field method.This redefines the potential field function and the repulsive force function,and then plans a shortest path around the obstacle,and the robot arm calculates the corresponding joint angle according to the path,so that the end can reach the target point without collision.Experimental simulation shows that the algorithm can jump out of the local optimal solution.Because of the LM algorithm,its iteration speed is faster.(4)This article is not only on the Robottool Box platform of Matlab,but also on the Robot Studio platform for simulation verification.The experimental results show that compared with other trajectory planning algorithms,the trajectory planning algorithm based on LM algorithm proposed in this paper has an iterative speed Fast,will not fall into the characteristics of the local optimal solution;in the obstacle avoidance experiment,the algorithm proposed in this paper enables the robot arm to reach the target point safely and without collision on the shortest path without colliding and needing to avoid obstacles,it also has good robustness. |
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