A review: On intelligent mobile robot path planning techniques

• Main Authors: Muhammad, Aisha, Ali, Mohammed A. H., Shanono, Ibrahim Haruna
• Format: Conference or Workshop Item
• Published: 2021
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.um.edu.my/35410/
• Institution: Universiti Malaya

Path planning is one of the vital and defining features of autonomous robots. Robot navigation is a process designed to avoid any hitch or obstacles to aim at a particular position. This paper presents a brief review of the intelligent robot navigation methods. A brief discussion on the approaches is made to understand the path planning techniques to identify their research gap. The artificial intelligence methods such as genetic algorithm (GA), fuzzy logic (FL), ant colony optimization (ACO), neural network (NN), firefly algorithm (FA), particle swarm optimization (PSO), bacterial foraging optimization (BFO), artificial bee colony (ABC), and other miscellaneous algorithms are reviewed. This paper further concludes with a discussion of the analysis of the reviewed articles and the challenges faced.