Article

Swarm Intelligence

, Volume 8, Issue 1, pp 1-33

Cooperative navigation in robotic swarms

  • Frederick DucatelleAffiliated withIDSIA, USI/SUPSI
  • , Gianni A. Di CaroAffiliated withIDSIA, USI/SUPSI Email author 
  • , Alexander FörsterAffiliated withIDSIA, USI/SUPSI
  • , Michael BonaniAffiliated withEPFL, ME A3 484 (Bâtiment ME)
  • , Marco DorigoAffiliated withIRIDIA, CoDE, ULB
  • , Stéphane MagnenatAffiliated withEPFL, ME A3 484 (Bâtiment ME)
  • , Francesco MondadaAffiliated withEPFL, ME A3 484 (Bâtiment ME)
  • , Rehan O’GradyAffiliated withIRIDIA, CoDE, ULB
  • , Carlo PinciroliAffiliated withIRIDIA, CoDE, ULB
    • , Philippe RétornazAffiliated withEPFL, ME A3 484 (Bâtiment ME)
    • , Vito TrianniAffiliated withIRIDIA, CoDE, ULB
    • , Luca M. GambardellaAffiliated withIDSIA, USI/SUPSI

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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.

Keywords

Swarm robotics Cooperative navigation Self-organization