Recent Advances of Hybrid Intelligent Systems Based on Soft Computing. Studies in Computational Intelligence ; Path Planning by Search Algorithms in Graph-Represented Workspaces
Springer, Cham, 2020
Online
Buch
Zugriff:
Path planning is an essential task in autonomous mobile robotics that demands to navigate following a minimum-cost path, which involves partitioning the landscape in nodes and the use of combinatorial optimization methods to find the optimal sequence of nodes to follow. Traditional algorithms such as the A* and Dijkstra are computationally efficient in landscapes with a reduced number of nodes. Most of the practical applications require to use a significantly large number of nodes up to the point that the problem might be computationally explosive. This work contributes to state-of-the-art with two heuristics for the A* algorithm that allows finding the optimal path in landscapes with a large number of nodes. The heuristics used the Euclidean and Manhattan distance in the estimation function. We present a comparative analysis of our proposal against the Dijkstra’s and A* algorithms. All the experiments were achieved using a simulation-platform specially designed for testing important algorithm features, such as the grid size, benchmark problems, the design of custom-made test sceneries, and others. Relevant results are drawn to continue working in this line.
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Recent Advances of Hybrid Intelligent Systems Based on Soft Computing. Studies in Computational Intelligence ; Path Planning by Search Algorithms in Graph-Represented Workspaces
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Autor/in / Beteiligte Person: | Vaneges Pérez, Iván Darío ; Montiel, Oscar ; Orozco Rosas, Ulises |
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Veröffentlichung: | Springer, Cham, 2020 |
Medientyp: | Buch |
ISBN: | 978-3-030-58728-4 (print) ; 3-030-58728-2 (print) |
DOI: | 10.1007/978-3-030-58728-4_4 |
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