Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/22154
Title: A genetic algorithm-inspired UUV path planner based on dynamic programming
Authors: Cheng, CT 
Fallahi, K
Leung, H
Tse, CK 
Issue Date: 2012
Source: IEEE transactions on systems, man, and cybernetics. Part C, Applications and reviews, 2012, v. 42, no. 6, 6135820, p. 1128-1134
Abstract: Path planning can be viewed as an optimization process in which an optimum path between two points is to be found under some predefined constraints. Some typical constraints are path length, fuel consumption, and path safety factor. Exact algorithms such as linear programming (LP) and dynamic programming (DP) are widely adopted in vehicle maneuvering systems. However, as the problem domain scales up, exact algorithms suffer from high computational complexity. In contrast, metaheuristic algorithms such as evolutionary algorithms (EA) and genetic algorithms (GA) can provide suboptimum solutions without the full understanding of the problem domain. Metaheuristic algorithms are capable of providing decent solutions within a finite period of time, even for large-scaled problems. In this paper, a GA-inspired unmanned underwater vehicle (UUV) path planner based on DP is proposed. Simulation results show that the proposed algorithm can outperform a GA-based UUV path planner in terms of speed and solution quality.
Keywords: Dynamic programming (DP)
genetic algorithms (GA)
optimization methods
path planning
underwater vehicle control
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE transactions on systems, man, and cybernetics. Part C, Applications and reviews 
ISSN: 1094-6977
DOI: 10.1109/TSMCC.2011.2180526
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