Advancements in UAV Path Planning from Traditional to Modern Algorithms

Unmanned Aerial Vehicles (UAVs) have recently been adapted to a variety of applications, bringing a variety of opportunities and challenges, including path planning, which is one of the main challenges that UAVs face during flight, where a UAV needs to plan a safe and optimal path that connects the starting point with a target destination in a complex and dynamic environment without human intervention. Many scholars were investigated to solve these complex NP-hard optimization problems with different types of algorithms. In this work, we present an ideal algorithm classification by dividing existing path planning approaches into traditional, model-based, sample-based, game theory, bio-inspired optimization, and AI-based approaches. Through this classification, we aim to minimize future research effort to choose the specific class for the chosen scenarios. This review paper is considered the first work that reviews and classifies existing UAV path planning algorithms in this way.