A simplified cost function heuristic applied to the A*-based path planning. (2016) - Silva, Jefferson B.B.; Siebra, Clauirton A.; Nascimento, Tiago P.
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.