Objects detection and location based on mask RCNN and stereo vision

Abstract

In order to improve the picking speed and accuracy of robot, the objects detection and localization algorithm based on Mask RCNN and stereo vision is designed to complete the autonomous detection and 3D spatial location of the target to be detected. Aiming at the problem that the detection accuracy of the neural network may be low and the object contour centroid estimation is not accurate, the ORB descriptor is used to confirm the target contour matching centroid. The experimental results show that the proposed algorithm can accurately accomplish the object detection and localization, and it is of great significance for the research of fully automatic picking robots.