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Hybrid Underwater Robot System Based on ROS

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Published:20 September 2019Publication History

ABSTRACT

Underwater Robots play an important role in a number of shallow and deep-water missions. In recent years, Underwater Robots system design has been an active field of engineering researches.

This paper proposes new system design for underwater vehicles combining the best features of both ROV (remotely operated vehicle) and AUV (autonomous underwater vehicle) technologies. The system based on ROS platform and Ardupilot software is equipped with two types of navigation system setup (autonomous navigation and teleoperation navigation) capable of realizing precise motion control, navigating while performing SLAM (Simultaneous Localization and Mapping) path-planning and obstacles avoidance.

References

  1. Budiyano, A (2009). Advances in unmanned underwater vehicles technologies: Modeling, control and guidance perspectives. Indian Journal of Marine Sciences, 38(3), 282--295.Google ScholarGoogle Scholar
  2. S. M. Zanoli, G. Conte (2003). Remotely operated vehicle depth control, Control Engineering Practice, 11(4), 453--459.Google ScholarGoogle ScholarCross RefCross Ref
  3. T. Hyakudome (2011). Design of Autonomous Underwater Vehicle, International Journal of Advanced Robotic Systems, 8(1), 131--139.Google ScholarGoogle ScholarCross RefCross Ref
  4. Bellavia F, Fanfani M, Colombo C (2017). Selective visual odometry for accurate AUV localization[J]. Autonomous Robots, 41(1), 133--143.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Armin Hornung, Kai M Wurm, Maren Bennewitz, Cyrill Stachniss, and Wolfram Burgard (2013). OctoMap: An Efficient Probabilistic 3D Mapping Framework based on Octrees. Autonomous Robots, 34(3), 189--206.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Henry P, Krainin M, Herbst E, et al (2012). RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments[J]. International Journal of Robotics Research, 31(5), 647--663.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Pire, Taihú, Fischer T, Castro, Gastón, et al (2017). S-PTAM: Stereo Parallel Tracking and Mapping[J]. Robotics and Autonomous Systems, (93), 27--42.Google ScholarGoogle Scholar
  8. Raúl Mur-Artal and Juan D Tardós (2017). ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras. IEEE Transactions on Robotics, 33(5), 1255--1262.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. S. G. G. G. W. Burgard (2012). A fully autonomous indoor quadrotor. IEEE Transaction on Robotics, 28(1), 90--100.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Hebecker T, Buchholz R, Ortmeier F (2015). Model-Based Local Path Planning for UAVs. [J]. Journal of Intelligent & Robotic Systems, 78(1), 127--142.Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Hybrid Underwater Robot System Based on ROS

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      • Published in

        cover image ACM Other conferences
        RICAI '19: Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence
        September 2019
        803 pages
        ISBN:9781450372985
        DOI:10.1145/3366194

        Copyright © 2019 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 20 September 2019

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        • research-article
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        • Refereed limited

        Acceptance Rates

        RICAI '19 Paper Acceptance Rate140of294submissions,48%Overall Acceptance Rate140of294submissions,48%

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