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

Jintao Xia, Jianning Chi, Chengdong Wu, Fengyu Zhao

发表年份
2022
引用次数
5

摘要

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%.

关键词

GRASPComputer visionArtificial intelligenceComputer scienceObject (grammar)RobotRegion of interestObject detectionPattern recognition (psychology)

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