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  1. Swarm Intelligence
  2. Swarm Intelligence : Volume 8
  3. Swarm Intelligence : Volume 8, Issue 1, March 2014
  4. Cooperative navigation in robotic swarms
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Swarm Intelligence : Volume 11
Swarm Intelligence : Volume 10
Swarm Intelligence : Volume 9
Swarm Intelligence : Volume 8
Swarm Intelligence : Volume 8, Issue 4, December 2014
Swarm Intelligence : Volume 8, Issue 3, September 2014
Swarm Intelligence : Volume 8, Issue 2, June 2014
Swarm Intelligence : Volume 8, Issue 1, March 2014
Cooperative navigation in robotic swarms
A generalized theoretical deterministic particle swarm model
Cache consensus: rapid object sorting by a robotic swarm
Swarm Intelligence : Volume 7
Swarm Intelligence : Volume 6
Swarm Intelligence : Volume 5
Swarm Intelligence : Volume 4
Swarm Intelligence : Volume 3
Swarm Intelligence : Volume 2
Swarm Intelligence : Volume 1

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Cooperative navigation in robotic swarms

Content Provider Springer Nature Link
Author Ducatelle, Frederick Caro, Gianni A. Förster, Alexander Bonani, Michael Dorigo, Marco Magnenat, Stéphane Mondada, Francesco O’Grady, Rehan Pinciroli, Carlo Rétornaz, Philippe Trianni, Vito Gambardella, Luca M.
Copyright Year 2013
Abstract We study cooperative navigation for robotic swarms in the context of a general event-servicing scenario. In the scenario, one or more events need to be serviced at specific locations by robots with the required skills. We focus on the question of how the swarm can inform its members about events, and guide robots to event locations. We propose a solution based on delay-tolerant wireless communications: by forwarding navigation information between them, robots cooperatively guide each other towards event locations. Such a collaborative approach leverages on the swarm’s intrinsic redundancy, distribution, and mobility. At the same time, the forwarding of navigation messages is the only form of cooperation that is required. This means that the robots are free in terms of their movement and location, and they can be involved in other tasks, unrelated to the navigation of the searching robot. This gives the system a high level of flexibility in terms of application scenarios, and a high degree of robustness with respect to robot failures or unexpected events. We study the algorithm in two different scenarios, both in simulation and on real robots. In the first scenario, a single searching robot needs to find a single target, while all other robots are involved in tasks of their own. In the second scenario, we study collective navigation: all robots of the swarm navigate back and forth between two targets, which is a typical scenario in swarm robotics. We show that in this case, the proposed algorithm gives rise to synergies in robot navigation, and it lets the swarm self-organize into a robust dynamic structure. The emergence of this structure improves navigation efficiency and lets the swarm find shortest paths.
Starting Page 1
Ending Page 33
Page Count 33
File Format PDF
ISSN 19353812
Journal Swarm Intelligence
Volume Number 8
Issue Number 1
e-ISSN 19353820
Language English
Publisher Springer US
Publisher Date 2013-11-23
Publisher Place Boston
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Swarm robotics Cooperative navigation Self-organization Artificial Intelligence (incl. Robotics) Computer Systems Organization and Communication Networks ApplicationMathematics/Computational Methods of Engineering Communications Engineering, Networks Computer Communication Networks
Content Type Text
Resource Type Article
Subject Artificial Intelligence
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