Efficient Deployment and Mission Timing of Autonomous Underwater Vehicles in Large-Scale Operations

TL;DR

This paper presents a routing and local path planning model for Autonomous Underwater Vehicles that enhances mission timing and robustness in turbulent environments using firefly optimization, suitable for large-scale operations.

Contribution

It introduces a cooperative routing and local path planning model with a re-routing procedure and firefly optimization for efficient, real-time AUV mission execution in complex underwater conditions.

Findings

Model achieves accurate mission timing considering battery limits.

System demonstrates robustness against water current variations.

Simulation confirms effectiveness in large-scale underwater operations.

Abstract

This study introduces a connective model of routing -- local path planning for Autonomous Underwater Vehicle (AUV) time efficient maneuver in long-range operations. Assuming the vehicle operating in a turbulent underwater environment, the local path planner produces the water-current resilient shortest paths along the existent nodes in the global route. A re-routing procedure is defined to re-organize the order of nodes in a route and compensate any lost time during the mission. The Firefly Optimization Algorithm (FOA) is conducted by both of the planners to validate the model's performance in mission timing and its robustness against water current variations. Considering the limitation over the battery life time, the model offers an accurate mission timing and real-time performance. The routing system and the local path planner operate cooperatively, and this is another reason for model's real-time performance. The simulation results confirms the model's capability in fulfillment of the expected criterion and proves its significant robustness against underwater uncertainties and variations of the mission conditions.