An Improved DFS-Based Path Planning Method for UAV Mapping Tasks

Résumé fourni par la source

With the widespread application of unmanned aerial vehicle (UAV) technology in the field of surveying and mapping, path planning capability has become a key factor restricting the quality of mapping operations and the level of energy consumption. To address issues such as high path redundancy, frequent directional changes, and excessive energy usage in large-scale UAV mapping tasks, this paper proposes a path planning method based on an improved Depth-First Search (DFS) algorithm. Specifically, a connectivity-based labeling function is introduced to constrain the path expansion direction and reduce invalid searches; in addition, a directional search function is designed to optimize the search order of neighboring nodes, thereby improving path continuity and planning efficiency. Simulation results show that the improved algorithm outperforms the traditional DFS in terms of path redundancy, number of turns, and total steps.

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