Title :
Communication using pheromone field for multiple robots
Author :
Fujisawa, Ryusuke ; Imamura, Hikaru ; Hashimoto, Takashi ; Matsuno, Fumitoshi
Author_Institution :
Dept. of Mech. Eng. & Intell. Syst., Univ. of Electro-Commun., Chofu
Abstract :
In this paper, we consider a issue that the reliable and the inexpensive communication method in swarm robotics. The ants forage for preys by using pheromone trails. They lay down the pheromone trails between preys and a nest. By detecting the trail pheromone, they can find the preys. Though they do not have excellent intelligence, they can communicate with each other and cooperate by adding information to the environment, like a pheromone. This communication method has a merit that an agent does not need to memorize the place of the preys. We consider to answer the issue that ldquoHow do the swarm robots communicate using pheromone trail?rdquo. We construct a swarm behavior simulator and develop swarm robots that communicate using the pheromone trail. We demonstrate the effectiveness of the communication using the pheromone trail by computer simulations and experiments using swarm robots. To realize this purpose, we design a swarm behavior algorithm, based on 4 perceptual signs (stimuli) and 3 effector signs (actions). In the simulations, an experimental field is discretized by computational grids, and evaporation and diffusion are phenomena of the pheromone modeled by discretized equations. The proposed algorithm is demonstrated by the simulation. Simulation result shows that proposed algorithms act effectively. Based on the simulation results, we set three robots, one nest and one prey in the flat experimental field. We observe three robotspsila behavior and the state of the environment for 20 minutes. The robots laid down the pheromone trail between the nest and the prey, and reinforced the pheromone trail many times. This fact means that swarm robots can realize the function of the chemical, indirect, plastic and local communication like ants by using the pheromone trail.
Keywords :
intelligent robots; multi-robot systems; computational grids; multiple robots; pheromone field; swarm behavior algorithm; swarm robotics; Collision avoidance; Computational modeling; Ethanol; Mobile robots; Robot kinematics; Robot sensing systems; Robots;
Conference_Titel :
Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on
Conference_Location :
Nice
Print_ISBN :
978-1-4244-2057-5
DOI :
10.1109/IROS.2008.4650971