Towards Energy-Aware Path Planning for AUV Swarms

Autonomous underwater vehicles (AUVs) are being researched for maritime applications such as ocean exploration and underwater maintenance. A swarm of AUVs is used for complex missions, with each AUV given a specific part of the mission. Energy-aware path planning is crucial for increasing operation time and reliability. This article discusses different path planning strategies for AUV swarms, comparing a particle swarm optimizer (PSO) and a greedy approach to determine the most energy-efficient route. One challenge here is to divide the total number of waypoints among the AUVs reasonably. For this purpose, we investigate a k-means algorithm and an extended variant of the PSO, in which we distribute the clusters dynamic according to a balanced metric. The aim is to find an algorithm that can be used for different applications and validated by different test scenarios focussing on energy consumption and mission fulfillment.

DDC Class

600: Technology

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Towards Energy-Aware Path Planning for AUV Swarms