Fast and Robust Pose Estimation Algorithm for Bin Picking Using Point Pair Feature

Abstract

Bin picking refers to picking up the objects randomly piled in the container (bin) and robotic bin picking is always used to improve the industrial production efficiency. A pose estimation algorithm is necessary to tell the poses of the objects to the robot. This paper proposes a pose estimation algorithm for bin picking using 3D point cloud data. Point Pair Feature algorithm is performed in a fast way to propose possible poses and the poses are verified by a voxel-based verification method. Iterative Closest Point is used to refine the result poses. Our algorithm is proved to be more accurate and faster than Curve Set Feature algorithm and Point Pair Feature algorithm, robust to occlusion and able to detect multiple poses in one scene.