Coverage Path Planning with Track Spacing Adaptation for Autonomous Underwater Vehicles
This addresses the problem of efficient seabed surveying for mine countermeasures using AUVs, representing an incremental improvement in path planning methods.
The paper tackles the mine countermeasures search problem for autonomous underwater vehicles by proposing a coverage path planning method that adapts track spacing to improve data quality, resulting in a 4.2% improvement in data quality for nearly 30% of the worst data and reduced area coverage gaps.
In this paper we address the mine countermeasures (MCM) search problem for an autonomous underwater vehicle (AUV) surveying the seabed using a side-looking sonar. We propose a coverage path planning method that adapts the AUV track spacing with the objective of collecting better data. We achieve this by shifting the coverage overlap at the tail of the sensor range where the lowest data quality is expected. To assess the algorithm, we collected data from three at-sea experiments. The adaptive survey allowed the AUV to recover from a situation where the sensor range was overestimated and resulted in reducing area coverage gaps. In another experiment,the adaptive survey showed a 4.2% improvement in data quality for nearly 30% of the 'worst' data.