Hybrid algorithms in path planning for autonomous navigation of unmanned aerial vehicle: a comprehensive review

Abstract Path planning for unmanned aerial vehicle (UAV) is the process of determining the path that travels through each location of interest within a particular area. There are numerous algorithms proposed and described in the publications to address UAV path planning problems. However, in order to handle the complex and dynamic environment with different obstacles, it is critical to utilize the proper fusion algorithms in planning the UAV path. This paper reviews some hybrid algorithms used in finding the optimal route of UAVs that developed in the last ten years as well as their advantages and disadvantages. The UAV path planning methods were classified into categories of hybrid algorithms based on traditional, heuristic, machine learning approaches. Criteria used to evaluate algorithms include execution time, total cost, energy consumption, robustness, data, computation, obstacle avoidance, and environment. The results of this study provide reference resources for researchers in finding the path for UAVs.