Study on an Optimization Algorithm for Unmanned Aerial Vehicle Surveying and Mapping Paths along the Coast

Topographic surveying and mapping is the basic operation of the waterway shoreline, which plays an important role in the collection of surface features, observation of renovation buildings, and accumulation of waterway evolution analysis data for waterway maintenance observation. At present, the surveying and mapping technology of drones is very mature, but there are still bottlenecks in flight time, surveying power consumption, and avoidance of flying obstacles, which affect the surveying and mapping results of the waterway shoreline. To extend the surveying and mapping time of the waterway shoreline, this paper proposes a dynamic programming algorithm. Firstly, based on the surveying and mapping operations of shoals, reefs, height differences, and siltation sections in the Yangtze River waterway, dynamic planning algorithm analysis is conducted based on the surveying and mapping routes of unmanned aerial vehicles. Divide the surveying and mapping path into three segments: start, process, and end. Refine the surveying and mapping path of each segment into four dynamic items, and construct a dynamic planning algorithm. Secondly, analyze and integrate each dynamic term to eliminate unsolvable eigenvalues, and obtain the optimal mapping path for effectiveness verification. The results indicate that the dynamic programming algorithm dynamically analyzes each segment of the mapping path, reduces the direction of path changes, improves the flight time of unmanned aerial vehicles, shortens the length of the mapping path, and reduces overall flight power consumption by adjusting the threshold in the mapping process.