000190825 001__ 190825
000190825 005__ 20190316235750.0
000190825 022__ $$a1935-3812
000190825 02470 $$2ISI$$a000332378200001
000190825 0247_ $$2doi$$a10.1007/s11721-013-0089-4
000190825 037__ $$aARTICLE
000190825 245__ $$aCooperative navigation in robotic swarms
000190825 269__ $$a2013
000190825 260__ $$bSpringer Verlag$$c2013
000190825 336__ $$aJournal Articles
000190825 520__ $$aWe 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.
000190825 6531_ $$aSwarm robotics
000190825 6531_ $$aCooperative navigation
000190825 6531_ $$aSelf-organization
000190825 6531_ $$a[MOBOTS]
000190825 700__ $$aDucatelle, Frederick
000190825 700__ $$aCaro, Di
000190825 700__ $$aGianni, A.
000190825 700__ $$0241015$$g120088$$aFörster, Alexander
000190825 700__ $$0241015$$g120088$$aBonani, Michael
000190825 700__ $$aDorigo, Marco
000190825 700__ $$0240589$$g102717$$aMagnenat, Stéphane
000190825 700__ $$0240589$$g102717$$aMondada, Francesco
000190825 700__ $$aO’Grady, Rehan
000190825 700__ $$aPinciroli, Carlo
000190825 700__ $$0244052$$g160180$$aRétornaz, Philippe
000190825 700__ $$aTrianni, Vito
000190825 700__ $$aGambardella, Luca M.
000190825 773__ $$j8$$tSwarm Intelligence$$k1$$q1-33
000190825 8564_ $$uhttps://infoscience.epfl.ch/record/190825/files/dtn_navigation-si-web.pdf$$zn/a$$s1674820$$yn/a
000190825 909C0 $$xU12367$$0252409$$pNCCR-ROBOTICS
000190825 909C0 $$pLSRO$$0252016
000190825 909CO $$qGLOBAL_SET$$pSTI$$particle$$ooai:infoscience.tind.io:190825
000190825 917Z8 $$x102717
000190825 917Z8 $$x102717
000190825 917Z8 $$x221818
000190825 937__ $$aEPFL-ARTICLE-190825
000190825 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000190825 980__ $$aARTICLE