Xie, Yongchang;
Nanlal, Cassandra;
Liu, Yuanchang;
(2024)
Reliable LiDAR-based ship detection and tracking for Autonomous Surface Vehicles in busy maritime environments.
Ocean Engineering
, 312
(Part-3)
, Article 119288. 10.1016/j.oceaneng.2024.119288.
Preview |
Text
Reliable LiDAR-based ship detection and tracking for Autonomous Surface Vehicles in busy maritime environments.pdf - Published Version Download (6MB) | Preview |
Abstract
Environmental perception is a crucial requirement of Autonomous Surface Vehicles (ASVs) if required to perform tasks safely in a dynamically complex operational environment. Most existing methods for ship detection rely on camera-based methods, which are sensitive to environmental conditions and cannot directly provide spatial location information related to detected targets. To overcome this limitation, we propose a LiDAR-based ship detection and tracking framework that can be applied to busy maritime environments. The proposed framework consists of two functional modules: a ship detection and multi-object tracking. For ship detection, a modularised network structure was adapted, allowing for ease of switching between different types of detection network to prioritise either detection accuracy, detection speed or a compromise of both, depending on the task requirements. A Kalman Filter-based multi-object tracking method is also implemented to compensate for any detections that may have been missed as a result of ship motions or occlusions, relying solely on the detection results. We also collected the first-ever real-world LiDAR dataset for maritime applications across the River Thames and marinas, including a range of ship types, with lengths ranging from 5 m up to 40 m, and different hull types. The datasets are organised in a similar manner to the KITTI datasets, which can be easily applied to the well-developed point cloud detection networks. Remarkably, our methods achieve an overall detection accuracy of 74.1% in the collected datasets. The proposed framework and dataset make LiDAR-based environmental perception feasible for implementation in ASVs and support development in the autonomous maritime navigation field.
| Type: | Article |
|---|---|
| Title: | Reliable LiDAR-based ship detection and tracking for Autonomous Surface Vehicles in busy maritime environments |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.oceaneng.2024.119288 |
| Publisher version: | https://doi.org/10.1016/j.oceaneng.2024.119288 |
| Language: | English |
| Additional information: | Copyright © 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | LiDAR-based perception; Ship detection; Deep learning; Object tracking; Autonomous Surface Vehicle |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10197444 |
Loading...
Loading...Loading...Loading...Archive Staff Only
 |
View Item |
