Abstract

Unmanned Aerial Vehicles (UAVs) are ideally suited for many real-world applications ranging from scientific to commercial, industrial, and military fields. Enhancing the efficiency of UAV-based missions through optimization techniques is of paramount significance. Unmanned Aerial Vehicles (UAVs) are ideally suited for many real-world applications ranging from scientific to commercial, industrial, and military fields. Enhancing the efficiency of UAV-based missions through optimization techniques is of paramount significance. In this regard, the path planning problem that refers to finding the best collision-free path between the start point and the destination by addressing temporal, physical, and geometric constraints is a key issue. In this paper, a review of recent path planning methods from different perspectives with a clear and comprehensive categorization is presented. This study provides a general taxonomy categorizing the existing works into classical approaches, soft-computing techniques, and hybrid methods. Here, a detailed analysis of the recent techniques as well as their advantages and limitations is offered. Additionally, it provides an overview of environment modeling methods, path structures, optimality criteria, completeness criteria, and current UAV simulators.

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