Deploying a networked set of robots is an effective way to serve applications in environments where human intervention is impossible or possess risks. For example, a team of robots can assist rescuers to map, navigate indoor hazardous areas in rescue operation. Collaboration among the robots is very essential in these applications in order to efficiently achieve the aimed goals in a timely manner. Realising such a collaborative operation autonomously in the absence of GPS services is a challenge. This study tackles this challenge assuming sensors/landmarks are present in the deployment area. Each sensor/landmark requires a specific number of robots to perform certain tasks. A spatial–temporal coverage solution is pursued to maintain connectivity and overcome the shortage of available robots. Dynamic coverage problem is formulated as potential fields where landmarks and nodes exert virtual forces among each other based on coverage demand and overlapped area. The proposed approach has been validated through extensive simulation using NS3 simulator and real experimentation using EV3 robots. The proposed approached has shown maximal task satisfaction compared with random waypoint and very close behaviour compared with a centralised approach (Hungarian method).

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Self-deployed wireless actor networks with maximal task satisfaction

References

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