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A 4.8x Faster FPGA-Based Iterative Closest Point Accelerator for Object Pose Estimation of Picking Robot Applications

Atsutake Kosuge, Keisuke Yamamoto, Yukinori Akamine, Taizo Yamawaki, T. Oshima

Year
2019
Citations
11

Abstract

An FPGA-based accelerator for the iterative-closest-point (ICP) algorithm has been proposed, which achieves 4.8-times-faster object-pose estimation by a picking robot compared with the state-of-the-art technique. Experiments of the proposed FPGA-based ICP accelerator using Amazon Picking Contest data sets have confirmed that the object-pose estimation by the ICP takes only 0.6 seconds, and the entire picking process takes 2.0 seconds with power consumption of 6.0 W.

Keywords

Field-programmable gate arrayComputer sciencePoseRobotObject (grammar)Computer visionArtificial intelligencePoint (geometry)Hardware accelerationIterative closest point

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