Project MAXCMAS - A Multi-objective Optimization Approach for COLREGs-compliant Path Planning of Autonomous Surface Vehicles verified on Networked Bridge Simulators’

Zakirul Bhuiyan, Liang Hu, Wasif Naeem, Eshan Rajabally, Graham Watson

Research output: Contribution to journalArticle

Abstract

This paper presents a multiobjective optimisation
approach for path planning of autonomous surface vehicles
(ASVs). A unique feature of the technique is the unification of
the Convention on the International Regulations for Preventing
Collisions at Sea (COLREGs) with good seamanship’s practice
alongwith hierarchical (rather than simultaneous) inclusion of
objectives. The requirements of collision avoidance are formulated
as mathematical inequalities and constraints in the
optimisation framework and thus collision-free manoeuvres and
COLREGs-compliant behaviours are provided in a seafarerlike
way. Specific expert knowledge is also taken into account
when designing the multiobjective optimisation algorithm. For
example, good seamanship reveals that if allowed, an evasive
manoeuvre with course changes is always preferred over one
with speed changes in practical maritime navigation. As a result,
a hierarchical sorting rule is designed to prioritize the objective
of course/speed change preference over other objectives such as
path length and path smoothness, and then incorporated into a
specific evolutionary algorithm called hierarchical multiobjective
particle swarm optimisation (H-MOPSO) algorithm. The HMOPSO
algorithm solves the real-time path planning problem
through finding solutions of the formulated optimisation problem.
The effectiveness of the proposed H-MOPSO algorithm is
demonstrated through both desktop and high-fidelity networked
bridge simulations.
Original languageEnglish
JournalIEEE Transactions on Intelligent Transportation Systems
Publication statusSubmitted - 1 Mar 2018

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Multiobjective optimization
Motion planning
Simulators
Collision avoidance
Sorting
Evolutionary algorithms
Navigation

Cite this

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title = "Project MAXCMAS - A Multi-objective Optimization Approach for COLREGs-compliant Path Planning of Autonomous Surface Vehicles verified on Networked Bridge Simulators’",
abstract = "This paper presents a multiobjective optimisationapproach for path planning of autonomous surface vehicles(ASVs). A unique feature of the technique is the unification ofthe Convention on the International Regulations for PreventingCollisions at Sea (COLREGs) with good seamanship’s practicealongwith hierarchical (rather than simultaneous) inclusion ofobjectives. The requirements of collision avoidance are formulatedas mathematical inequalities and constraints in theoptimisation framework and thus collision-free manoeuvres andCOLREGs-compliant behaviours are provided in a seafarerlikeway. Specific expert knowledge is also taken into accountwhen designing the multiobjective optimisation algorithm. Forexample, good seamanship reveals that if allowed, an evasivemanoeuvre with course changes is always preferred over onewith speed changes in practical maritime navigation. As a result,a hierarchical sorting rule is designed to prioritize the objectiveof course/speed change preference over other objectives such aspath length and path smoothness, and then incorporated into aspecific evolutionary algorithm called hierarchical multiobjectiveparticle swarm optimisation (H-MOPSO) algorithm. The HMOPSOalgorithm solves the real-time path planning problemthrough finding solutions of the formulated optimisation problem.The effectiveness of the proposed H-MOPSO algorithm isdemonstrated through both desktop and high-fidelity networkedbridge simulations.",
author = "Zakirul Bhuiyan and Liang Hu and Wasif Naeem and Eshan Rajabally and Graham Watson",
year = "2018",
month = "3",
day = "1",
language = "English",
journal = "IEEE Transactions on Intelligent Transportation Systems",
issn = "1524-9050",
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AU - Bhuiyan, Zakirul

AU - Hu, Liang

AU - Naeem, Wasif

AU - Rajabally, Eshan

AU - Watson, Graham

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AB - This paper presents a multiobjective optimisationapproach for path planning of autonomous surface vehicles(ASVs). A unique feature of the technique is the unification ofthe Convention on the International Regulations for PreventingCollisions at Sea (COLREGs) with good seamanship’s practicealongwith hierarchical (rather than simultaneous) inclusion ofobjectives. The requirements of collision avoidance are formulatedas mathematical inequalities and constraints in theoptimisation framework and thus collision-free manoeuvres andCOLREGs-compliant behaviours are provided in a seafarerlikeway. Specific expert knowledge is also taken into accountwhen designing the multiobjective optimisation algorithm. Forexample, good seamanship reveals that if allowed, an evasivemanoeuvre with course changes is always preferred over onewith speed changes in practical maritime navigation. As a result,a hierarchical sorting rule is designed to prioritize the objectiveof course/speed change preference over other objectives such aspath length and path smoothness, and then incorporated into aspecific evolutionary algorithm called hierarchical multiobjectiveparticle swarm optimisation (H-MOPSO) algorithm. The HMOPSOalgorithm solves the real-time path planning problemthrough finding solutions of the formulated optimisation problem.The effectiveness of the proposed H-MOPSO algorithm isdemonstrated through both desktop and high-fidelity networkedbridge simulations.

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