Ant algorithms for discrete optimization
Artificial Life
Vision for Mobile Robot Navigation: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Autonomous Robots
Swarm-Bot: A New Distributed Robotic Concept
Autonomous Robots
Multi-robot mobility enhanced hop-count based localization in ad hoc networks
Robotics and Autonomous Systems
Coverage, exploration, and deployment by a mobile robot and communication network
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Chain based path formation in swarms of robots
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Multirobot systems: a classification focused on coordination
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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
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We investigate the use of telecommunications to support the control of a swarm of small mobile robots. The robots need to service events that present themselves in different locations within a confined area. We focus on the task of robot navigation: how can robots of the swarm assist each other to reach event locations. We present two solutions based on the use of routing information set up in a mobile ad hoc network created among the robots. Communication in this network relies on an infrared range and bearing device, which is able to transfer data between two robots as well as to make estimates of the relative distance and angle between them. Using this device, one can relate links in the communication network to relative geographic location information. We then use an ad hoc network routing protocol to dynamically find and maintain paths between a robot and an event location in the communication network and use them to guide the robot to its goal. An important advantage of our approach is that robots can transparently help each other for navigation without having to adapt their own movements, so that they can be involved in independent tasks of their own.