Robot Grasping Detection in Object Overlapping Scenes Based on Multi-Stage ROI Extraction

Abstract

In multi-object stacking scenes, it is difficult for robots to detect and grasp objects. We propose a new robot grasp detection algorithm Multi-Stage ROI Grasp Detection(MSROI-GD). MSROI-GD uses multi-stage extracted ROI features to detect objects and grasp. Our algorithm can effectively filter and utilize ROI. Experimental results show that the improved MSROI-GD improves the accuracy of the original ROI-GD algorithm by 4.3%, and exceeds the current state-of-the-art algorithm by 0.5% in the overlapping scenes of objects in the VMRD dataset. At the same time, using our grasp detection algorithm on the Cornell grasp dataset still has good results. Robot experiments show that MSROI-GD can help robots grasp object in multi-object scenes with a success rate of 85%.