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R-DFS: A Coverage Path Planning Approach Based on Region Optimal Decomposition
| Content Provider | MDPI |
|---|---|
| Author | Tang, Gang Tang, Congqiang Zhou, Hao Claramunt, Christophe Men, Shaoyang |
| Copyright Year | 2021 |
| Description | 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. |
| Starting Page | 1525 |
| e-ISSN | 20724292 |
| DOI | 10.3390/rs13081525 |
| Journal | Remote Sensing |
| Issue Number | 8 |
| Volume Number | 13 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-04-15 |
| Access Restriction | Open |
| Subject Keyword | Remote Sensing Transportation Science and Technology Coverage Path Planning Region Optimal Decomposition Depth-first-search Algorithm |
| Content Type | Text |
| Resource Type | Article |
