Research on Environmental 3D Reconstruction and Obstacle Avoidance Algorithm of Industrial Robots
Aiming at solving the problem of obstacle avoidance and motion planning for robots in unknown environments,a method of 3D reconstruction and obstacle avoidance for industrial robot arm based on visual was researched.The hand-eye sys-tem consisted of the depth camera(RealSense D435i)and the manipulator.Firstly,the posture of the target object was calculated by using the coordinate of the feature point on the ArUcomark obtained by the depth camera.Then,the3Dreconstruction method is improved.By fusing the end pose of the manipulator and multi-frame point cloud data,the environment is reconstructed with higher precision in three dimensions as the obstacle space for subsequent planning.Finally,the improved algorithm of Rapidly Expanding Random Tree(RRT)was applied to the obstacle avoidance and motion planning of the manipulator.At the same time,a simulation and control platform was built for verification.The experimental result shows that the accuracy of 3D modeling is maintained within 8mm,the success rate of obstacle avoidance is 96.5%,and the average planning time is 1.2s,which verifies the feasibility of this method.
NETL
NSTL
万方数据
维普
