COLREGs-Informed RRT* for Collision Avoidance of Marine Crafts

Thomas Thuesen Enevoldsen; Christopher Clarc Reinartz; Roberto Galeazzi

doi:10.1109/ICRA48506.2021.9560909

COLREGs-Informed RRT* for Collision Avoidance of Marine Crafts

Thomas Thuesen Enevoldsen, Christopher Clarc Reinartz, Roberto Galeazzi

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

The paper proposes novel sampling strategies to compute the optimal path alteration of a surface vessel sailing in close quarters. Such strategy directly encodes the rules for safe navigation at sea, by exploiting the concept of minimal ship domain to determine the compliant region where the path deviation is to be generated. The sampling strategy is integrated within the optimal rapidly-exploring random tree algorithm, which minimizes the length of the path deviation. Further, the feasibility of the path with respect to the steering characteristics of own ship is verified by ensuring that the position of the new waypoints respects the minimum turning radius of the vessel. The proposed sampling strategy brings a significant performance improvement both in terms of optimal cost, computational speed and convergence rate.

Original language	English
Title of host publication	Proceedings of 2021 IEEE International Conference on Robotics and Automation
Number of pages	7
Publisher	IEEE
Publication date	2021
ISBN (Print)	978-1-7281-9078-5
DOIs	https://doi.org/10.1109/ICRA48506.2021.9560909
Publication status	Published - 2021
Event	2021 IEEE International Conference on Robotics and Automation - Xi’an International Convention and Exhibition Center, Xi’an, China Duration: 30 May 2021 → 5 Jun 2021

Conference

Conference	2021 IEEE International Conference on Robotics and Automation
Location	Xi’an International Convention and Exhibition Center
Country/Territory	China
City	Xi’an
Period	30/05/2021 → 05/06/2021

UN SDGs

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

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10.1109/ICRA48506.2021.9560909

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

Cite this

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title = "COLREGs-Informed RRT* for Collision Avoidance of Marine Crafts",

abstract = "The paper proposes novel sampling strategies to compute the optimal path alteration of a surface vessel sailing in close quarters. Such strategy directly encodes the rules for safe navigation at sea, by exploiting the concept of minimal ship domain to determine the compliant region where the path deviation is to be generated. The sampling strategy is integrated within the optimal rapidly-exploring random tree algorithm, which minimizes the length of the path deviation. Further, the feasibility of the path with respect to the steering characteristics of own ship is verified by ensuring that the position of the new waypoints respects the minimum turning radius of the vessel. The proposed sampling strategy brings a significant performance improvement both in terms of optimal cost, computational speed and convergence rate.",

author = "Enevoldsen, {Thomas Thuesen} and Reinartz, {Christopher Clarc} and Roberto Galeazzi",

year = "2021",

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language = "English",

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booktitle = "Proceedings of 2021 IEEE International Conference on Robotics and Automation",

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AB - The paper proposes novel sampling strategies to compute the optimal path alteration of a surface vessel sailing in close quarters. Such strategy directly encodes the rules for safe navigation at sea, by exploiting the concept of minimal ship domain to determine the compliant region where the path deviation is to be generated. The sampling strategy is integrated within the optimal rapidly-exploring random tree algorithm, which minimizes the length of the path deviation. Further, the feasibility of the path with respect to the steering characteristics of own ship is verified by ensuring that the position of the new waypoints respects the minimum turning radius of the vessel. The proposed sampling strategy brings a significant performance improvement both in terms of optimal cost, computational speed and convergence rate.

U2 - 10.1109/ICRA48506.2021.9560909

DO - 10.1109/ICRA48506.2021.9560909

M3 - Article in proceedings

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BT - Proceedings of 2021 IEEE International Conference on Robotics and Automation

PB - IEEE

T2 - 2021 IEEE International Conference on Robotics and Automation

Y2 - 30 May 2021 through 5 June 2021

ER -

COLREGs-Informed RRT* for Collision Avoidance of Marine Crafts

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ShippingLab Autonomy

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