RGBD Object Recognition and Flat Area Analysis Method for Manipulator Grasping

Grasping guided by visual recognition and positioning is a practical requirement of discrete automation. This paper proposes a general method of using RGBD image recognition, which can recognize object with only one RGB template photograph of the target object, calculate 3D coordinates and pose, and guide the 6 DOF manipulator to grasp object. SIFT(Scale Invariant Feature Transform) is used to extract feature points of template image and real-time scene image and complete matching. Matched feature points are used as seed points to segment target objects in depth image. This method is fast and requires less prior knowledge. In order to optimize the grasping, this paper uses the Shape Index method to locate the flat area on the object which is most suitable for the suction cup. This method can make the grasping system automatically adapt to various objects and overcome the problems of overlapping and partial occlusion.