Multi-Depth Uniform Coverage Path Planning for Unmanned Surface Vehicle Surveying
Izaro Goienetxea , Jaime Valls Miro
AI summary
Problem
Traditional bathymetric survey path planning relies on fixed geometric patterns that assume a constant sonar footprint, causing significant coverage gaps and inefficiencies when seafloor depths vary. This forces operators into time-consuming manual adjustments and compromises data quality in complex coastal terrains.
Approach
The proposed MDNUC algorithm uses coarse prior depth maps to partition the survey area into depth-based regions, dynamically adapts the multibeam echo sounder's beam angle, and generates a single continuous, non-revisiting path optimized for uniform seafloor coverage.
Key results
- Achieves >99% coverage on synthetic terrains, surpassing traditional boustrophedon methods (max 75%)
- Reaches >92% coverage in realistic harbor simulations, outperforming boustrophedon sweeps (<65%)
- Eliminates cellular decomposition for scalable, automated path generation in complex areas
- Provides open-source algorithm implementation for autonomous marine deployment
Why it matters
Enables highly efficient, fully automated bathymetric surveys for unmanned surface vehicles in complex coastal environments, reducing operational costs and improving data quality for navigation and environmental monitoring.
Abstract
This paper introduces a novel automatic coverage path planning algorithm for bathymetry surveying with un- manned surface vehicles. The detection range of the mapping sensor employed - a multibeam echo sounder - is heavily influenced by local seafloor depths. Hence, a path designed to uniformly cover the sea surface does not guarantee uniform coverage of the seafloor. Yet this is currently the typical process for bathymetric surveys, with the simplistic boustrophedon scheme along manually selected waypoints at constant depths being the most widespread planner used. The proposed scheme incorporates coarse prior depth information to pre-process the target region and adaptively guide path generation and sensing range configuration. By explicitly accounting for depth variations, the proposed algorithm designs a coverage path with optimised spacing between survey passes that adjusts the sensing beam aperture to achieve more consistent seafloor coverage. The proposed method is shown to offer significant improvements in both synthetic and real-world scenarios. Val- idations in challenging synthetic terrains achieves coverage ra- tios beyond 99%, a marked improvement when compared with traditional boustrophedon paths revealing a maximum 75% coverage. The same trend appears in realistic simulations using real bathymetric data from a coastal harbour, with coverage reaching over 92%, and significantly surpassing boustrophedon sweeps with coverage rates below 65%. Beyond improved performance, the scheme also brings a fully automated design, suitable for autonomous marine vehicles, thus offering practical utilities for real-world applications.