Differential Evolution for Efficient AUV Path Planning in Time Variant Uncertain Underwater Environment
S. Mahmoud Zadeh, D. M.W. Powers, A. Yazdani, K. Sammut, A Atyabi

TL;DR
This paper presents a Differential Evolution-based path planning method for autonomous underwater vehicles that efficiently navigates complex, time-variant, and uncertain underwater environments, ensuring safety and real-time performance.
Contribution
It introduces a novel DE-based approach tailored for 3D AUV path planning in realistic, dynamic underwater settings, handling obstacles, currents, and vehicle constraints.
Findings
The method achieves feasible, collision-free paths in complex environments.
It demonstrates robustness against strong and variable ocean currents.
The approach operates with low computational time suitable for real-time deployment.
Abstract
The AUV three-dimension path planning in complex turbulent underwater environment is investigated in this research, in which static current map data and uncertain static-moving time variant obstacles are taken into account. Robustness of AUVs path planning to this strong variability is known as a complex NP-hard problem and is considered a critical issue to ensure vehicles safe deployment. Efficient evolutionary techniques have substantial potential of handling NP hard complexity of path planning problem as more powerful and fast algorithms among other approaches for mentioned problem. For the purpose of this research Differential Evolution (DE) technique is conducted to solve the AUV path planning problem in a realistic underwater environment. The path planners designed in this paper are capable of extracting feasible areas of a real map to determine the allowed spaces for deployment,…
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Taxonomy
TopicsMaritime Navigation and Safety · Robotic Path Planning Algorithms · Underwater Vehicles and Communication Systems
