UUV's Hierarchical DE-based Motion Planning in a Semi Dynamic Underwater Wireless Sensor Network

TL;DR

This paper presents a hierarchical, multi-layered motion planning framework for Unmanned Underwater Vehicles (UUVs) in semi-dynamic underwater sensor networks, utilizing Differential Evolution algorithms for efficient, real-time path planning amidst environmental uncertainties.

Contribution

It introduces a novel multilayered mission planner integrating global and local path planning with an environmental sub-layer, employing Differential Evolution for adaptive, real-time navigation in complex underwater environments.

Findings

Framework achieves efficient mission timing.

Demonstrates resilience against environmental disturbances.

Ensures safe and reliable UUV deployment.

Abstract

This paper describes a reflexive multilayered mission planner with a mounted energy efficient local path planner for Unmanned Underwater Vehicle's (UUV) navigation throughout the complex subsea volume in a time-variant semi-dynamic operation network. The UUV routing protocol in Underwater Wireless Sensor Network (UNSW) is generalized with a homogeneous Dynamic Knapsack-Traveler Salesman Problem emerging with an adaptive path planning mechanism to address UUV's long-duration missions on dynamically changing subsea volume. The framework includes a base layer of global path planning, an inner layer of local path planning and an environmental sub-layer. Such a multilayer integrated structure facilitates the framework to adopt any algorithm with real-time performance. The evolutionary technique known as Differential Evolution algorithm is employed by both base and inner layers to examine the performance of the framework in efficient mission timing and its resilience against the environmental disturbances. Relying on reactive nature of the framework and fast computational performance of the DE algorithm, the simulations show promising results and this new framework guarantees a safe and efficient deployment in a turbulent uncertain marine environment passing through a proper sequence of stations considering various constraint in a complex environment.