Research And Simulation Of Industrial Robot Path Planning Algorithm

The problem of robot path planning has always been a hot and difficult problem in the field of robot research.The purpose of industrial robot path planning is to find a collision-free path that can move the robot from the initial position to the target position in a complex environment with obstacles.Facing the coming of the intelligent era,studying the path planning of industrial robots has a positive significance for promoting the development of intelligent robots.For the path planning of six-axis industrial robots,this paper improves RRT(Rapid-exploration Random Tree)algorithm and proposes two improved methods.Perform smooth processing and speed planning on the planned path to ensure that the robot moves smoothly and reduce the impact damage to the motor.(1)The D-H parameter method is used to model the six-axis industrial robot,and its positive kinematics and inverse kinematics equations are derived.The Matlab Robotics toolbox was used to model and analyze the robot and verify the correctness of the deduced forward and inverse kinematics equations.The singularity and working space of the robot are analyzed.(2)Based on the strategy of segmented replanning,an algorithm SR-RRT(Segmentation Re-planning Rapidly-Exploring Random Tree)is proposed to find a better path,the algorithm makes the path converge to a more optimal way through multiple planning optimization.The path evaluation function is used to discard inferior paths and memorize inferior nodes,and guide the algorithm to search for a better global path.Using a divide-and-conquer strategy,the path is divided into two segments during the replanning stage,and then planned separately and then merged.Using Matlab and Open RAVE(Open Robotics Automation Virtual Environment)for simulation experiments,the results show that SR-RRT can obtain a better path in a shorter time than other RRT * series algorithms.(3)In response to the problem of the large number of path nodes obtained by the RRT series of algorithms,this paper proposes an improved bidirectional RRT algorithm,BI-RRT(Bidirectional Rapidly-Exploring Random Tree)based on the RRT-Connect algorithm.By introducing a "base node" to transform the random tree organization,it can effectively reduce the number of nodes in the path.This can make the algorithm more time-saving in the path pruning process,and the resulting path is more conducive to the robot's motion control.Using Matlab and Open RAVE for simulation experiments,the results show that BI-RRT is more suitable for solving the path planning problem of industrial robots.(4)Aiming at the problem that the paths planned by RRT series algorithms cannot be directly used for robot motion control,this paper uses an improved cubic B-spline curve fitting algorithm to smooth the paths in the robot joint space,and perform joint space velocity planning on the obtained cubic B-spline curve.This paper proposes a uniform time interval planning method,a particle swarm optimization algorithm-based time planning method and a non-uniform time interval planning method.Among them,the non-uniform time interval planning method is calculated on the premise that the trajectory obtained by velocity planning meets the kinematic constraints It is simple,and the planned trajectory duration is short.