3D object detection and pose estimation from depth image for robotic bin picking

Abstract

In this paper, we present a system for automatic object detection and pose estimation from a single depth map containing multiple objects for bin-picking applications. The proposed object detection algorithm is based on matching the keypoints extracted from the depth image by using the RANSAC algorithm with the spin image descriptor. In the proposed system, we combine the keypoint detection and the RANSAC algorithm to detect the objects, followed by the ICP algorithm to refine the 3D pose estimation. In addition, we implement the proposed algorithm on the GPGPU platform to speed-up the computation. Experimental results on simulated depth data are shown to demonstrate the proposed system.