Distributed coordination of simulated robots based on self-organization

被引:21
作者
Baldassarre, Gianluca [1 ]
Parisi, Domenico [1 ]
Nolfi, Stefano [1 ]
机构
[1] CNR, ISTC, LARAL, I-00185 Rome, Italy
关键词
genetic algorithms; neural networks; collective robotics; traction sensor; conformism; positive feedback; integration of behaviors; physical constraints; scalability;
D O I
10.1162/artl.2006.12.3.289
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Distributed coordination of groups of individuals accomplishing a common task without leaders, with little communication, and on the basis of self-organizing principles, is an important research issue within the study of collective behavior of animals, humans, and robots. The article shows how distributed coordination allows a group of evolved, physically linked simulated robots (inspired by a robot under construction) to display a variety of higlily coordinated basic behaviors such as collective motion, collective obstacle avoidance, and collective approach to light, and to integrate them in a coherent fashion. In this way the group is capable of searching and approaching a lighted target in an environment scattered with obstacles, furrows, and holes, where robots acting individually fail. The article shows how the emerged coordination of the group relies upon robust self-organizing principles (e.g., positive feedback) based on a novel sensor that allows the single robots to perceive the group's "average" motion direction. The article also presents a robust solution to a difficult coordination problem, which might also be encountered by some organisms, caused by the fact that the robots have to be capable of moving in any direction while being physically connected. Finally the article shows how the evolved distributed coordination mechanisms scale very well with respect to the number of robots, the way in which robots are assembled, the structure of the environment, and several other aspects.
引用
收藏
页码:289 / 311
页数:23
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