Shortest Path Planning for Energy-Constrained Mobile Platforms Navigating on Uneven Terrains

Ganganath, N, Cheng, C, Fernando, T, Lu, H and Tse, C 2018, 'Shortest Path Planning for Energy-Constrained Mobile Platforms Navigating on Uneven Terrains', IEEE Transactions on Industrial Informatics, vol. 14, no. 9, pp. 4264-4272.

Document type: Journal Article
Collection: Journal Articles

Title Shortest Path Planning for Energy-Constrained Mobile Platforms Navigating on Uneven Terrains
Author(s) Ganganath, N
Cheng, C
Fernando, T
Lu, H
Tse, C
Year 2018
Journal name IEEE Transactions on Industrial Informatics
Volume number 14
Issue number 9
Start page 4264
End page 4272
Total pages 9
Publisher Institute of Electrical and Electronics Engineers
Abstract Finding a shortest feasible path between two given locations is a common problem in many real-world applications. Previous studies have shown that mobile platforms would consume excessive energy when moving along shortest paths on uneven terrains, which often consist of rapid elevation changes. Mobile platforms powered by portable energy sources may fail to follow such paths due to the limited energy available. This paper proposes a new heuristic search algorithm called constraints satisfying A* (CSA*) to find solutions to such resource constrained shortest path problems. When CSA* is guided by admissible heuristics, it guarantees to find a globally optimal solution to a given constrained search problem if such a solution exists. When CSA* is guided by consistent heuristics, it is optimally efficient over a class of equally informed admissible constrained search algorithms with respect to the set of paths expanded. Test results obtained using real terrain data verify the applicability of the proposed algorithm in shortest path planning for energy-constrained mobile platforms on uneven terrains.
Subject Analysis of Algorithms and Complexity
Control Systems, Robotics and Automation
Keyword(s) (CSA*)
Constraints satisfying A
Heuristic search
Multiple resource constraints
Outdoor navigation
Shortest paths
DOI - identifier 10.1109/TII.2018.2844370
Copyright notice © 2018 IEEE.
ISSN 1551-3203
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Citation counts: TR Web of Science Citation Count  Cited 7 times in Thomson Reuters Web of Science Article | Citations
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