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Underwater autonomous grasping robot based on multi-stage Cascade DetNet

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Abstract

At present, underwater exploration and salvage, underwater archaeology, and other underwater operations still mainly rely on professional underwater operators. Considering that artificial underwater operation is faced with the problems of small exploration scope, poor working environment, and low work efficiency, it is the future trend to use robots to replace manual underwater operation in related fields. Most of the current underwater robots are artificial remote-controlled, which lack intelligent detection and autonomous grasping system. In this paper, a grasping robot equipped with an AI computing platform is developed to enable the autonomous grasping of underwater targets by using stereo vision technology. For the problem of difficult detection due to the small size and occlusion of underwater targets, this paper proposes Cascade DetNet, which can improve recognition accuracy. The experimental results show that our proposed method achieves the best performance on URPC dataset compared with several mainstream methods. In addition, we also carry out the autonomous grasping of seafood in a real marine environment to verify the autonomous grasping performance of underwater vehicles.

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Notes

  1. ROI is the intersection of Anchor and label divided by the union of Anchor and label.

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Authors and Affiliations

  1. Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing Artificial Intelligence Institute, the Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China

    Yong Zhang, Yongli Hu & Baocai Yin

  2. Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing, 100124, China

    Chengyang Zhang & Bo Li

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  1. Yong Zhang
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  2. Chengyang Zhang
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  3. Bo Li
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  4. Yongli Hu
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  5. Baocai Yin
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Correspondence to Yong Zhang.

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The research project is partially supported by National Key R\&D Program of China (No. 2021ZD0111902), National Natural Science Foundation of China (No. 62072015, U19B2039, U21B2038).

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Zhang, Y., Zhang, C., Li, B. et al. Underwater autonomous grasping robot based on multi-stage Cascade DetNet. Artif Life Robotics 28, 448–459 (2023). https://doi.org/10.1007/s10015-023-00865-z

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  • DOI: https://doi.org/10.1007/s10015-023-00865-z

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