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Droplet: Towards Autonomous Underwater Assembly of Modular Structures

Abstract

This paper presents a first low-cost autonomous robotic system for underwater assembly of mortarless structures. The long-term goal is to enable the construction of large-scale underwater structures; such as retaining walls and artificial reefs. The approach follows the principle of co-design; the 2-DOF manipulator and blocks are designed to complement the localization and control strategies. The blocks and gripper are designed with a connector geometry that removes error during pickup of blocks and drop assembly. This error correction feature allows a simplification of localization and control; which are based on fiducial markers on custom platforms. We developed the proposed system on a low-cost heavily modified BlueROV2 autonomous vehicle — which we call Droplet — with a two-degree of freedom hand that can open and close a gripper and rotate over the yaw. We performed extensive experiments in the pool to evaluate each component and the system as a whole. Results showed a 100% success rate in dropping blocks in the presence of some localization and control errors and the assembly of several different 3D structures composed of up to eight blocks.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Reinforcement Learning
🐣 Hot Topic Early Bird — error correction
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio