Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Designing emergent behaviors: from local interactions to collective intelligence
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Stigmergy, self-organization, and sorting in collective robotics
Artificial Life
Cooperative Mobile Robotics: Antecedents and Directions
Autonomous Robots
Self-Organization in Biological Systems
Self-Organization in Biological Systems
Soft Computing and Fuzzy Logic
IEEE Software
Autonomous Robots
Swarm robotics: from sources of inspiration to domains of application
SAB'04 Proceedings of the 2004 international conference on Swarm Robotics
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Swarm robotics is a decentralized control architecture, where global behavior emerges as a result of local interactions between neighboring robots. The deficiency of the swarm behavior model is the stochastic nature of movement patterns, which reduces its applicability, when precise maneuvering is needed. This paper alleviates this problem by introducing fuzzy manual control of a multi-robot system utilizing the swarm behavior model. The built-in swarm behavior controls low level tasks such as formation keeping and obstacle avoidance. A fuzzy controller works as an intelligent mechanism for tuning the manual control signal received by the robots. The main advantages of the presented algorithm are: 1) deliberating the operator from low level maneuvering tasks; 2) single operator control of multi-robot group; 3) robustness, flexibility and scalability. The presented architecture was implemented and tested in a simulation environment. The introduced system can significantly improve the performance of search and rescue operations as well as exploration of dangerous environments.