A simplified cost function heuristic applied to the A*-based path planning
by Jefferson B.B. Silva; Clauirton A. Siebra; Tiago P. Nascimento
International Journal of Computer Applications in Technology (IJCAT), Vol. 54, No. 2, 2016

Abstract: An important task for mobile robots is autonomous navigation, where a robot travels between two locations without the need of human intervention. This task can be described as a planning path problem, whose purpose is to define sequential segments of state transitions from an initial to a final goal. This paper investigates a family of trajectory generation algorithms (A*), which are commonly used in path planning for static environments, stressing their main properties. Then, it is presented as a simplified cost function heuristic that is used to optimise the results presented in the original approaches. The comparison of the main algorithms is carried out via a set of experiments, which show that the proposed heuristic reduces the computational cost of the search, the amount of expanded cells and mainly the time required to locate targets.

Online publication date: Fri, 02-Sep-2016

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