AUV Rendezvous Online Path Planning in a Highly Cluttered Undersea Environment Using Evolutionary Algorithms
Somaiyeh Mahmoud Zadeh, Amir Mehdi Yazdani, Karl Sammut, David M.W, Powers

TL;DR
This paper develops and compares evolutionary algorithm-based path planning methods for autonomous underwater vehicles to efficiently and robustly achieve rendezvous in cluttered, dynamic undersea environments, accounting for obstacles and currents.
Contribution
It introduces a novel reactive planner integrating evolutionary algorithms with environmental awareness for AUV rendezvous in complex undersea terrains.
Findings
The proposed planner demonstrates high robustness in dynamic environments.
Evolutionary algorithms effectively optimize AUV paths considering currents and obstacles.
The methods improve autonomy and success rate of underwater rendezvous missions.
Abstract
In this study, a single autonomous underwater vehicle (AUV) aims to rendezvous with a submerged leader recovery vehicle through a cluttered and variable operating field. The rendezvous problem is transformed into a nonlinear optimal control problem (NOCP) and then numerical solutions are provided. A penalty function method is utilized to combine the boundary conditions, vehicular and environmental constraints with the performance index that is final rendezvous time.Four evolutionary based path planning methods namely particle swarm optimization (PSO), biogeography-based optimization (BBO), differential evolution (DE) and Firefly algorithm (FA) are employed to establish a reactive planner module and provide a numerical solution for the proposed NOCP. The objective is to synthesize and analysis the performance and capability of the mentioned methods for guiding an AUV from loitering point…
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Taxonomy
TopicsRobotic Path Planning Algorithms · Underwater Vehicles and Communication Systems · Maritime Navigation and Safety
