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A Comparative Study Between Hopfield Neural Network and A* Path Planning Algorithms for Mobile Robot
Kodgule S.A, Das A,
Published in Springer Singapore
Volume: 517
Pages: 33 - 48
Path planning is an important aspect of any mobile robot navigation to find a hazard-free path and an optimal path. Currently, the A* algorithm is considered to be one of the prominent algorithms for path planning in a known environment. However, with the rise of neural networks and machine learning, newer promising algorithms are emerging in this domain. Our work compares one such algorithm namely the Hopfield neural network-based path planning algorithm with A* in a static environment. Both the Hopfield network and the A* algorithm were implemented while minimizing the total run times of the programs. For this, both the algorithms were run in MATLAB environment and a set of mazes were then executed and their run times were compared. Based on the study, the A* algorithm fared better and the Hopfield network showed promising results with scope for further reduction in its run time. © Springer Nature Singapore Pte Ltd. 2017.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing Artificial Intelligence and Evolutionary Computations in Engineering Systems
PublisherData powered by TypesetSpringer Singapore
Open Access0