R-DFS: A Coverage Path Planning Approach Based on Region Optimal Decomposition

• Main Authors: Gang Tang, Congqiang Tang, Hao Zhou, Christophe Claramunt, Shaoyang Men
• Format: Article
• Language: English
• Published: MDPI AG 2021-04-01
• Series: Remote Sensing
• Subjects: coverage path planning; region optimal decomposition; depth-first-search algorithm; remote sensing
• Online Access: https://www.mdpi.com/2072-4292/13/8/1525

Most Coverage Path Planning (CPP) strategies based on the minimum width of a concave polygonal area are very likely to generate non-optimal paths with many turns. This paper introduces a CPP method based on a Region Optimal Decomposition (ROD) that overcomes this limitation when applied to the path planning of an Unmanned Aerial Vehicle (UAV) in a port environment. The principle of the approach is to first apply a ROD to a Google Earth image of a port and combining the resulting sub-regions by an improved Depth-First-Search (DFS) algorithm. Finally, a genetic algorithm determines the traversal order of all sub-regions. The simulation experiments show that the combination of ROD and improved DFS algorithm can reduce the number of turns by 4.34%, increase the coverage rate by more than 10%, and shorten the non-working distance by about 29.91%. Overall, the whole approach provides a sound solution for the CPP and operations of UAVs in port environments.