Design and Development of the MeCO Open-Source Autonomous Underwater Vehicle

2025-03-13

AI Summary

High barriers to entry and a lack of low-cost, open-source autonomous underwater vehicle (AUV) platforms hinder research in underwater human–robot interaction (UHRI). Method: This paper proposes and implements MeCO—a full-stack, open-source, mid-to-low-cost AUV specifically designed for UHRI. Its architecture uniquely integrates underwater LiFi optical communication, acoustic interaction, stereo vision, and omnidirectional LED display. Leveraging ROS 2 and Docker, MeCO achieves hardware–software decoupling, combining Jetson-based edge AI, STM32 microcontrollers running RT-Thread real-time OS, and modular mechatronic design. Contribution/Results: The system undergoes rigorous validation across simulation, pool, and near-shore environments. All design files, firmware, and software are publicly released under open-source licenses. MeCO substantially reduces both the cost and technical barriers for UHRI and AUV development, has already enabled multiple interaction experiments and educational deployments, and provides a scalable, cross-environmentally validated, standardized open platform for marine robotics research.

Technology Category

• Humans and AI: Interaction Techniques and Devices
• Intelligent Robots: Human-Robot Interaction
• Machine Learning: Hardware-aware ML

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Economics, Online Markets and Human Computation: Research challenges in human and human-AI computation

Abstract

We present MeCO, the Medium Cost Open-source autonomous underwater vehicle (AUV), a versatile autonomous vehicle designed to support research and development in underwater human-robot interaction (UHRI) and marine robotics in general. An inexpensive platform to build compared to similarly-capable AUVs, the MeCO design and software are released under open-source licenses, making it a cost effective, extensible, and open platform. It is equipped with UHRI-focused systems, such as front and side facing displays, light-based communication devices, a transducer for acoustic interaction, and stereo vision, in addition to typical AUV sensing and actuation components. Additionally, MeCO is capable of real-time deep learning inference using the latest edge computing devices, while maintaining low-latency, closed-loop control through high-performance microcontrollers. MeCO is designed from the ground up for modularity in internal electronics, external payloads, and software architecture, exploiting open-source robotics and containerarization tools. We demonstrate the diverse capabilities of MeCO through simulated, closed-water, and open-water experiments. All resources necessary to build and run MeCO, including software and hardware design, have been made publicly available.

Problem

• Develops an open-source, cost-effective AUV for underwater research.
• Enables real-time deep learning and low-latency control in marine robotics.
• Provides modular design for electronics, payloads, and software architecture.

Innovation

• Open-source design and software for cost-effective AUV
• Real-time deep learning with edge computing devices
• Modular electronics and software for extensibility