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A fast search algorithm based on image pyramid for robotic grasping

Guangli Ren, Zhenzhou Shao, Yong Guan, Ying Qu, Jindong Tan, Hongxing Wei, Guofeng Tong

Year
2017
Citations
5

Abstract

To improve the search efficiency of robotic grasping detection, this paper presents a novel search algorithm based on the image pyramid. It significantly reduces the search space for grasping position detection using the coarse-to-fine strategy. The proposed method searches the positions from the top layer of the pyramid, and initializes the search area at the next layer. The sparse automatic encoder is employed to construct the model which is used to evaluate the grasp quality. The experimental results demonstrate that the proposed search algorithm can improve efficiency of the robotic grasping detection with the comparative performance on the grasp quality.

Keywords

GRASPPyramid (geometry)Computer scienceArtificial intelligenceConstruct (python library)EncoderComputer visionSearch algorithmPosition (finance)Image (mathematics)

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