Action Decision Strategy of Simulation Robot Fish Based on Ant Colony Algorithm

Autor: Xue Le Jia, Yan Song Deng, Xu Qiong Yang
Rok vydání: 2013
Předmět:
Zdroj: Applied Mechanics and Materials. :949-954
ISSN: 1662-7482
DOI: 10.4028/www.scientific.net/amm.341-342.949
Popis: In order to achieve the quick and accurate adjustment of the robot fish, there are two plans, which are based on ant-colony-algorithm movement strategy. These plans are aimed at 2D robot fish in the ant colony algorithm, and the key judgment of the robot fish relies on the branches of physic matters, together with the best match of the fish in its current speed. However, according to the dynamic algorithm project, the feedback of dynamic variable movement can process adjustment automatically. In every period, these two examples by which the 2D Simulation results show the robot fish can be adjusted on the policy path. To achieve optimal combination of speed and direction, the shortest time has a strong ability to adapt effectively to meet the simulation of robot fish or action of the action decision-making.
Databáze: OpenAIRE