Title :
Robots Active Olfaction Based on Improved Genetic Algorithm
Author :
Zhi-Biao Shi ; Jiang-Bo Sun
Author_Institution :
Northeast Dianli Univ., Changchun, China
Abstract :
Robots active olfaction based on Genetic algorithm, in order to make the robot car plume in a specific environment, can be faster and more accurate to find the odor source, through the genetic algorithm crossover and mutation operator improved, the formation of a new improved genetic algorithm. In the five assumptions, will improve the genetic algorithm is applied to the robot active olfaction study, simulation results show that the genetic algorithm with the traditional comparison, the robot car can be faster and more accurate in finding the odor plume source.
Keywords :
electronic noses; genetic algorithms; robots; crossover operator; improved genetic algorithm; mutation operator; odor plume source finding; odor source; robot active olfaction; robot car plume; robots active olfaction; Algebra; Genetic algorithms; Mathematical model; Robot sensing systems; Search problems; Simulation; improved genetic algorithm; plume model; robots active olfaction;
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2013 5th International Conference on
Conference_Location :
Mathura
DOI :
10.1109/CICN.2013.136