A Review of Path Planning Algorithms

In recent decades, automation and robotics have seen remarkable progress, as seen in projects like the Google driverless car and advanced Unmanned Aerial Vehicles (UAVs) with “sense and avoid” capabilities, emphasizing a push for greater autonomy. Path planning algorithms play a vital role in various domains, including mobile robots, UAVs, and autonomous vehicles, by determining safe, efficient, collision-free, and cost-effective routes from start to finish. Choosing the right algorithm is crucial, depending on factors like the robot’s geometry and computational constraints, whether static/holonomic or dynamic/non-holonomic systems. This highlights the need for improved path planning algorithms. It is essential to have a deep understanding of contemporary solutions to achieve these goals. The objective of this paper is to provide an overview of the current state-of-the-art in path planning across different fields. Additionally, we place particular emphasis on widely-used algorithms capable of meeting real-time constraints and accommodating dynamic re-planning.