From Tom Thumb to the Dockers: some experiments with foraging robots
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
An Behavior-based Robotics
Map-based navigation in mobile robots
Cognitive Systems Research
Map-based navigation in mobile robots
Cognitive Systems Research
A fully decentralized approach for incremental perception
Proceedings of the 1st international conference on Robot communication and coordination
Robot Navigation in a Networked Swarm
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part I
Wireless Communications for Distributed Navigation in Robot Swarms
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Robotics and Autonomous Systems
Teamwork in self-organized robot colonies
IEEE Transactions on Evolutionary Computation
From solitary to collective behaviours: decision making and cooperation
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Subsumption architecture for enabling strategic coordination of robot swarms in a gaming scenario
ICAIS'11 Proceedings of the Second international conference on Adaptive and intelligent systems
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In this paper we analyse a previously introduced swarm intelligence control mechanism used for solving problems of robot path formation. We determine the impact of two probabilistic control parameters. In particular, the problem we consider consists in forming a path between two objects which an individual robot cannot perceive simultaneously. Our experiments were conducted in simulation. We compare four different robot group sizes with up to 20 robots, and vary the difficulty of the task by considering five different distances between the objects which have to be connected by a path. Our results show that the two investigated parameters have a strong impact on the behaviour of the overall system and that the optimal set of parameters is a function of group size and task difficulty. Additionally, we show that our system scales well with the number of robots.