http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Real-time Velocity Optimization of a Group of Autonomous Members via Ant Colony Optimization (ACO)
Ramin Vatankhah,Shahram Etemadi,Aria Alasty,Mehrdad Boroushaki,Gholamreza Vossoughi 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In this paper, the agent velocity in robotic swarm was determined by using Ant Colony optimization (ACO) algorithm to maximize the swarm center velocity. First briefly we present an analytical study of swarm motion in a quasi static environment, in which, motion of each member is being affected by interactive forces and an agent. Interactive effects on each member could be attractive or repulsive due to being far from or close to other members respectively. It is also considered that field of view of all members is limited, i.e. even the agent accesses its local information. Ant colony algorithm is a mathematical model of ants" behaviour in finding the shortest path between nest and food. The agent velocity in robotic swarm was determined by using ACO to maximize the swarm center velocity. The results show the high ability of this evolutionary algorithm in solving complicated dynamic optimization problems.