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

David Widhalm, Cory Ohnsted, Corey Knutson, Demetrious Kutzke, Sakshi Singh, Rishi Mukherjee, Grant Schwidder, Ying-Kun Wu, Junaed Sattar

TL;DR

This work tackles the need for a low-cost, open-source AUV capable of underwater human-robot interaction (UHRI) by introducing MeCO, a platform costing around $10$K with a modular tri-tube hull that achieves $6$-DoF motion using $5$ thrusters and onboard edge DL inference on a $Nvidia Jetson Orin NX$. It fuses UHRI interfaces (OLEDs, HREyes, SIREN, gesture recognition, and AR tag control) with a ROS 2/micro-ROS software stack and a Unity-based simulator to accelerate prototyping and field testing. The authors validate MeCO through simulated, closed-water, and open-water experiments, including Visual SLAM, trash/object detection with deep networks, and end-to-end UHRI missions involving divers. Overall, MeCO represents an open-source, modular, and extensible AUV that lowers barriers to UHRI research and collaboration in underwater robotics while providing a reusable platform for rapid development and replication.

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.

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

TL;DR

This work tackles the need for a low-cost, open-source AUV capable of underwater human-robot interaction (UHRI) by introducing MeCO, a platform costing around K with a modular tri-tube hull that achieves -DoF motion using thrusters and onboard edge DL inference on a . It fuses UHRI interfaces (OLEDs, HREyes, SIREN, gesture recognition, and AR tag control) with a ROS 2/micro-ROS software stack and a Unity-based simulator to accelerate prototyping and field testing. The authors validate MeCO through simulated, closed-water, and open-water experiments, including Visual SLAM, trash/object detection with deep networks, and end-to-end UHRI missions involving divers. Overall, MeCO represents an open-source, modular, and extensible AUV that lowers barriers to UHRI research and collaboration in underwater robotics while providing a reusable platform for rapid development and replication.

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.

Paper Structure

This paper contains 9 sections, 11 figures.

Figures (11)

  • Figure 1: The MeCO AUV operating during an open-water field trial in the Caribbean Sea off the coast of Barbados.
  • Figure 2: MeCO CAD model highlighting dimensions, power, sensing, and propulsion features.
  • Figure 3: Rear view perspective of MeCO, showing cable routing to distribute power, PWM signals, Ethernet, and common ground between all three tubes.
  • Figure 4: OLED displays on MeCO. (a) A customizable experiment menu is displayed on the side OLED. (b) The front OLED display showing "State IDLE," during one such experiment.
  • Figure 5: MeCO subsystems diagram showing connections between side and center tube components.
  • ...and 6 more figures