A review: On path planning strategies for navigation of mobile robot

TLDR

The paper rigorously studies mobile robot navigation techniques, examining classical and reactive approaches to understand path‑planning strategies across environments and identify research gaps. It reviews classical methods such as cell decomposition, roadmap, and artificial potential field, and reactive methods including genetic algorithm, fuzzy logic, neural networks, firefly, particle swarm, ant colony, bacterial foraging, artificial bee colony, cuckoo search, shuffled frog leaping, and other miscellaneous algorithms. Reactive approaches are more robust and perform better in all terrains than classical methods, are often used as hybrids, and are the most popular for mobile robot path planning, as shown by comparative tables and charts of strategy frequencies.

Abstract

This paper presents the rigorous study of mobile robot navigation techniques used so far. The step by step investigations of classical and reactive approaches are made here to understand the development of path planning strategies in various environmental conditions and to identify research gap. The classical approaches such as cell decomposition (CD), roadmap approach (RA), artificial potential field (APF); reactive approaches such as genetic algorithm (GA), fuzzy logic (FL), neural network (NN), firefly algorithm (FA), particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization (BFO), artificial bee colony (ABC), cuckoo search (CS), shuffled frog leaping algorithm (SFLA) and other miscellaneous algorithms (OMA) are considered for study. The navigation over static and dynamic condition is analyzed (for single and multiple robot systems) and it has been observed that the reactive approaches are more robust and perform well in all terrain when compared to classical approaches. It is also observed that the reactive approaches are used to improve the performance of the classical approaches as a hybrid algorithm. Hence, reactive approaches are more popular and widely used for path planning of mobile robot. The paper concludes with tabular data and charts comparing the frequency of individual navigational strategies which can be used for specific application in robotics.