Article
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Target Localization and Grasping of NAO robot Based on YOLOv8 network and Monocular Ranging
Version 1
: Received: 30 August 2023 / Approved: 31 August 2023 / Online: 31 August 2023 (09:52:07 CEST)
A peer-reviewed article of this Preprint also exists.
Jin, Y.; Shi, Z.; Xu, X.; Wu, G.; Li, H.; Wen, S. Target Localization and Grasping of NAO Robot Based on YOLOv8 Network and Monocular Ranging. Electronics 2023, 12, 3981. Jin, Y.; Shi, Z.; Xu, X.; Wu, G.; Li, H.; Wen, S. Target Localization and Grasping of NAO Robot Based on YOLOv8 Network and Monocular Ranging. Electronics 2023, 12, 3981.
Abstract
As a typical visual positioning system, monocular ranging is widely used in various fields. However, when the distance increases, there is a greater error. YOLOv8 network has the advantages of fast recognition speed and high accuracy. This paper proposes a method by combining YOLOv8 network recognition with a monocular ranging method to achieve target localization and grasping for the NAO robots. By establishing a visual distance error compensation model and applying it to correct the estimation results of the monocular distance measurement model, the accuracy of the NAO robot's long-distance monocular visual positioning is improved. Additionally, a grasping control strategy based on pose interpolation is proposed. Throughout, the proposed method's advantage in measurement accuracy was confirmed via experiments, and the grasping strategy has been implemented to accurately grasp the target object.
Keywords
NAO robot; YOLOv8 network; monocular ranging; error compensation model; pose interpolation
Subject
Computer Science and Mathematics, Robotics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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