ATRON: Autonomous trash retrieval for oceanic neatness

The subject of this article is the development of an unmanned surface vehicle (USV) for the removal of floating debris. A twin-hulled boat with four thrusters placed at the corners of the vessel is used for this purpose. The trash is collected in a storage space through a timing belt driven by an electric motor. The debris is accumulated in a funnel positioned at the front of the boat and subsequently raised through this belt into the garbage bin. The boat is equipped with a spherical camera, a long-range 2D LiDAR, and an inertial measurement unit (IMU) for simultaneous localization and mapping (SLAM). The floating debris is identified from rectified camera frames using YOLO, while the LiDAR and IMU concurrently provide the USV's odometry. Visual methods are utilized to determine the location of debris and obstacles in the 3D environment. The optimal order in which the debris is collected is determined by solving the orienteering problem, and the planar convex hull of the boat is combined with map and obstacle data via the Open Motion Planning Library (OMPL) to perform path planning. Pure pursuit is used to generate the trajectory from the obtained path. Limits on the linear and angular velocities are experimentally estimated, and a PID controller is tuned to improve path following. The USV is evaluated in an indoor swimming pool containing static obstacles and floating debris.

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Publication Details

Journal
Frontiers in Robotics and AI
Published
2026-01-22
DOI
https://doi.org/10.3389/frobt.2025.1718177
Primary Topic
Maritime Navigation and Safety
Type
article
Field-Weighted Citation Impact
0.00

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article

ATRON: Autonomous trash retrieval for oceanic neatness

Anthony Tzes, Hyunjin Jang, Behruz Erkinov, Jana Awadalla et al.
Frontiers in Robotics and AI
Maritime Navigation and Safety
article

ATRON: Autonomous trash retrieval for oceanic neatness

Anthony Tzes, Hyunjin Jang, Behruz Erkinov, Jana Awadalla, John Abanes
article en

Abstract

The subject of this article is the development of an unmanned surface vehicle (USV) for the removal of floating debris. A twin-hulled boat with four thrusters placed at the corners of the vessel is used for this purpose. The trash is collected in a storage space through a timing belt driven by an electric motor. The debris is accumulated in a funnel positioned at the front of the boat and subsequently raised through this belt into the garbage bin. The boat is equipped with a spherical camera, a long-range 2D LiDAR, and an inertial measurement unit (IMU) for simultaneous localization and mapping (SLAM). The floating debris is identified from rectified camera frames using YOLO, while the LiDAR and IMU concurrently provide the USV's odometry. Visual methods are utilized to determine the location of debris and obstacles in the 3D environment. The optimal order in which the debris is collected is determined by solving the orienteering problem, and the planar convex hull of the boat is combined with map and obstacle data via the Open Motion Planning Library (OMPL) to perform path planning. Pure pursuit is used to generate the trajectory from the obtained path. Limits on the linear and angular velocities are experimentally estimated, and a PID controller is tuned to improve path following. The USV is evaluated in an indoor swimming pool containing static obstacles and floating debris.

Frontiers in Robotics and AIVol. 12
New York University Abu Dhabi (AE), Centre for Artificial Intelligence and Robotics (IN), Egyptian Consulting & Trading Co. Ltd (EG), Virginia Tech (US)
New York University Abu Dhabi
Life below water
Openalex Percentile: Top 81%
Maritime Navigation and Safety
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