A Comprehensive Analysis of Path Planning Strategies Employed for Mobile Robots

Abstract

Path planning is the core of the field of mobile robots. In order to solve the problem of finding the optimal solution, experts have conducted extensive research on it. The document offers a concise overview of rigorously conducted research on prevalent path planning approaches for mobile robots up to this point. There are essentially two main categories of path planning methods for mobile robots: Classical methods and Heuristic methods. I have provided a more detailed classification of these methods: (1) Classical methods, (2) Heuristic Search algorithms, (3) Artificial Intelligence algorithms, (4) Bio-inspired algorithms. Classical methods overly rely on static environments and cannot be applied to practical situations, therefore path planning requires innovative methods. Bio-inspired algorithms are a hot topic in path planning methods, and many studies have innovated on the basis of basic bionic algorithms. Nowadays, Artificial Intelligence algorithms represented by artificial neural networks have gradually become the focus of path planning research due to their high adaptability and robustness. This paper investigates the basic principles, advantages and limitations of each method in the above classification, as well as new algorithms extended based on heuristic methods. In conclusion, this paper offers a succinct overview of the present research status on path planning for mobile robots and explores potential future directions in this domain.