Title :
A genetic algorithm based approach to search optimal assembly sequences for autonomous robotic assembly
Author :
Qianli Zhao ; Jiayi Mu ; Feiling Yang ; Ting Li ; Ying Wang
Author_Institution :
Dept. of Electr. & Mechatron. Eng., Southern Polytech. State Univ., Marietta, GA, USA
Abstract :
A Genetic Algorithm (GA) based approach is proposed in this paper to search optimal assembly sequences in a robotic autonomous assembly task. In particular, the chromosome definition, the operations of crossover, copy and mutation and a specific fitness table are presented. Some simulation results are employed to validate the effectiveness of the proposed approach. The simulation results also indicate that the modified GA algorithm proposed in this paper has better performance than the traditional GA algorithm.
Keywords :
genetic algorithms; robotic assembly; autonomous robotic assembly; chromosome definition; genetic algorithm; optimal assembly sequences; Assembly; Biological cells; Genetic algorithms; History; Robotic assembly; Robots; Simulation; Autonomous Assembly; Genetic Algorithms; Robots;
Conference_Titel :
SOUTHEASTCON 2014, IEEE
Conference_Location :
Lexington, KY
DOI :
10.1109/SECON.2014.6950735