Xinheng Yuan, Hao Yu, Houlin Zhang, Li Zheng, Erbao Dong*, Heng’an Wu*
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 281-301, 2022, DOI:10.32604/cmes.2022.021383
Abstract Robotic grasping is an essential problem at both the household and industrial levels, and unstructured objects
have always been difficult for grippers. Parallel-plate grippers and algorithms, focusing on partial information of
objects, are one of the widely used approaches. However, most works predict single-size grasp rectangles for fixed
cameras and gripper sizes. In this paper, a multi-scale grasp detector is proposed to predict grasp rectangles with
different sizes on RGB-D or RGB images in real-time for hand-eye cameras and various parallel-plate grippers.
The detector extracts feature maps of multiple scales and conducts predictions on each scale independently. To
guarantee independence… More >
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