Autonomous perception method of multi-degree-of-freedom industrial robot arm trajectory

Abstract

In this study, a novel autonomous sensing method of multi-degree-of-freedom industrial robot arm trajectory is proposed. The research takes the distance sensor to collect environmental data, and takes the point cloud data scanned by 3D laser as the basis. The environment model of multi-degree-of-freedom industrial robotic arm is established by Iterative Closest Point (ICP). Then the target object is calibrated by binocular imaging technology. Subsequently, angle of each joint of multi-degree-of-freedom industrial robotic arm is calculated to determine the spatial attitude of the robotic arm. In addition, 3D LiDAR is installed at the end of the robotic arm, and the end trajectory of multi-degree-of-freedom industrial robotic arm is sensed autonomously by using the optimal function. The proposed method has advantages of high accuracy and short sensing time in autonomous sensing of multi-degree-of-freedom industrial robot arm trajectory.