Grounding-aware RRT* for Path Planning and Safe Navigation of Marine  Crafts in Confined Waters

Thomas T. Enevoldsen; Roberto Galeazzi

doi:10.1016/j.ifacol.2021.10.093

Grounding-aware RRT* for Path Planning and Safe Navigation of Marine Crafts in Confined Waters

Thomas T. Enevoldsen, Roberto Galeazzi

Research output: Contribution to journal › Conference article › Research › peer-review

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Abstract

The paper presents a path planning algorithm based on RRT* that addresses the risk of grounding during evasive manoeuvres to avoid collision. The planner achieves this objective by integrating a collective navigation experience with the systematic use of water depth information from the electronic navigational chart. Multivariate kernel density estimation is applied to historical AIS data to generate a probabilistic model describing seafarer's best practices while sailing in confined waters. This knowledge is then encoded into the RRT* cost function to penalize path deviations that would lead own ship to sail in shallow waters. Depth contours satisfying the own ship draught define the actual navigable area, and triangulation of this non-convex region is adopted to enable uniform sampling. This ensures the optimal path deviation.

Original language	English
Book series	IFAC-PapersOnLine
Volume	54
Issue number	16
Pages (from-to)	195-201
ISSN	2405-8963
DOIs	https://doi.org/10.1016/j.ifacol.2021.10.093
Publication status	Published - 2021
Event	13^th IFAC Conference on Control Applications in Marine Systems, Robotics, and Vehicles - Online event Duration: 22 Sep 2021 → 24 Sep 2021 Conference number: 13 https://cams-2021.com

Conference

Conference	13^th IFAC Conference on Control Applications in Marine Systems, Robotics, and Vehicles
Number	13
Location	Online event
Period	22/09/2021 → 24/09/2021
Internet address	https://cams-2021.com

Keywords

Path planning
Collision and grounding avoidance
Kernel density estimation
AIS

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.ifacol.2021.10.093

FulltextAccepted author manuscript, 1.72 MB

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Full text

ShippingLab Autonomy
Blanke, M., Galeazzi, R., Dittmann, K., Hansen, S., Papageorgiou, D., Nalpantidis, L., Schöller, F. E. T. S., Plenge-Feidenhans'l, M. K., Hansen, N., Andersen, R. H., Becktor, J. B., Enevoldsen, T. T., Dagdilelis, D., Karstensen, P. I. H., Nielsen, R. E., Garde, J., Ravn, O., Christin, L. P. E. & Nielsen, R. E.
01/04/2019 → 31/12/2022
Project: Research

Cite this

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abstract = "The paper presents a path planning algorithm based on RRT* that addresses the risk of grounding during evasive manoeuvres to avoid collision. The planner achieves this objective by integrating a collective navigation experience with the systematic use of water depth information from the electronic navigational chart. Multivariate kernel density estimation is applied to historical AIS data to generate a probabilistic model describing seafarer's best practices while sailing in confined waters. This knowledge is then encoded into the RRT* cost function to penalize path deviations that would lead own ship to sail in shallow waters. Depth contours satisfying the own ship draught define the actual navigable area, and triangulation of this non-convex region is adopted to enable uniform sampling. This ensures the optimal path deviation.",

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