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

Patle, B.K and Babu Loganathan, Ganesh and Pandey, Anish and Parh, D.R.K and Jagadeesh, A (2019) A review: On path planning strategies for navigation of mobile robot. Defence Technology, 15 (4). pp. 582-606. ISSN 22149147

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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.

Item Type: Article
Uncontrolled Keywords: Mobile robot navigation,Path planning, Classical approaches, Reactive approaches, Artificial intelligence
Subjects: Engineering > Computer engineering
Engineering > Mechatronics engineering and machinery
Engineering > TK Electrical engineering
Depositing User: ePrints deposit
Date Deposited: 16 Dec 2020 09:19
Last Modified: 05 Dec 2022 07:15
URI: http://eprints.tiu.edu.iq/id/eprint/261

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