Autonomous Underwater Robotic Grasping Research Based on Navigation and Hierarchical Operation

Cong Wang, Qifeng Zhang, Xiaohui Wang, Shida Xu, Yvan Petillot, Sen Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes a new framework for the autonomous underwater operation of underwater vehicle manipulator systems (UVMS), which is modular, standardized, and hierarchical. The framework consists of three subsystems: perception, navigation, and grasping. The perception module is based on an underwater stereo vision system, which provides effective environment and target information for the navigation and grasping modules. The navigation module is based on ORBSLAM and acoustic odometry, which generates the global map and plans a trajectory for the first initial stage. The grasping module generates the target grasping pose based on the extracted point cloud and the current robot state, and then executes the grasping task based on the motion planner. The proposed system is tested to perform several underwater target grasping tasks in a water tank, demonstrating the effectiveness of the system.

Original languageEnglish
Title of host publication7th Asia-Pacific Conference on Intelligent Robot Systems 2022
PublisherIEEE
Pages176-182
Number of pages7
ISBN (Electronic)9781665485197
DOIs
Publication statusPublished - 18 Aug 2022
Event7th Asia-Pacific Conference on Intelligent Robot Systems 2022 - Tianjin, China
Duration: 1 Jul 20223 Jul 2022

Conference

Conference7th Asia-Pacific Conference on Intelligent Robot Systems 2022
Abbreviated titleACIRS 2022
Country/TerritoryChina
CityTianjin
Period1/07/223/07/22

Keywords

  • deep learning
  • navigation
  • underwater autonomous grasping
  • underwater robot

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Mechanical Engineering
  • Control and Optimization

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