Authors: Jefferson B.B. Silva; Clauirton A. Siebra; Tiago P. Nascimento
Addresses: Laboratory of Embedded Systems and Robotics, Federal University of Paraiba, Joao Pessoa, Paraiba, Brazil ' Laboratory of Embedded Systems and Robotics, Federal University of Paraiba, Joao Pessoa, Paraiba, Brazil ' Laboratory of Embedded Systems and Robotics, Federal University of Paraiba, Joao Pessoa, Paraiba, Brazil
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.
Keywords: pathfinder; heuristics; cost function; robot path planning; mobile robots; autonomous navigation; robot navigation; trajectory generation.
International Journal of Computer Applications in Technology, 2016 Vol.54 No.2, pp.96 - 105
Available online: 29 Aug 2016Full-text access for editors Access for subscribers Purchase this article Comment on this article