Optimal Time-Efficient UAV Area Coverage Path Planning Based on Raster Map

Abstract

In the original area coverage path planning algorithm, the generated paths are often slow and inefficient due to the diversity of task areas. In this paper, we propose an optimal time-efficient unmanned aerial vehicles (UAV) area coverage method based on raster maps, which enables it to perform better in practical application scenarios. Our work improves the original approach by replacing the previous angle-cost optimization strategy with optimal timing, and also conducts practical testing and modeling of UAVs, and finally experimental tests show that our approach is more time-efficient. On top of this, we also propose two pruning strategies, the first one is to discard those paths that are already far beyond the value during the calculation by continuously updating the minimum path consumption time, and the second one is to avoid erroneous path calculation by finding unreachable uncovered free grids in time during the calculation through the dead zone marker matrix. This paper also optimizes the path cost calculation to prevent the need to recalculate the previous path cost for each cost calculation. The above measures result in a reduction of the algorithm time computation by about 48.88%.