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Adaptive Path Planning for Depth Constrained Bathymetric Mapping with an Autonomous Surface Vessel

2016/03/21 by Troy Wilson, Stefan B. Williams, Wilson, Troy +2 · 1 citation
Computer Science · Engineering · #68T40 #FOS: Computer and information sciences #I.2.9 #Maritime Navigation and Safety #Robotic Path Planning Algorithms #Robotics (cs.RO) #Robotics and Sensor-Based Localization #Ship Hydrodynamics and Maneuverability #Underwater Vehicles and Communication Systems #acm:68T40 #cs.RO #msc:68T40

paper · pdf · doi:10.48550/arxiv.1603.06324

21 pages, 9 Figures, 1 Table. Submitted to The Journal of Field Robotics

openalex publication_date 2016/03/21 · arxiv created 2016/03/31 · arxiv updated 2016/04/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper describes the design, implementation and testing of a suite of algorithms to enable depth constrained autonomous bathymetric (underwater topography) mapping by an Autonomous Surface Vessel (ASV). Given a target depth and a bounding polygon, the ASV will find and follow the intersection of the bounding polygon and the depth contour as modeled online with a Gaussian Process (GP). This intersection, once mapped, will then be used as a boundary within which a path will be planned for coverage to build a map of the Bathymetry. Methods for sequential updates to GP's are described allowing online fitting, prediction and hyper-parameter optimisation on a small embedded PC. New algorithms are introduced for the partitioning of convex polygons to allow efficient path planning for coverage. These algorithms are tested both in simulation and in the field with a small twin hull differential thrust vessel built for the task.

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