Abstract. We consider a swarm of robots equipped with an infrared range and bearing device that is able both to make estimates of the relative distance and angle between two robots in line-of-sight and to transfer data between them. Through the infrared range and bearing device, the robots create a line-of-sight mobile ad hoc network. We investigate different ways to implement a swarm-level distributed navigation function exploiting the routing information gathered within this network. In the scenario we consider, a number of different events present themselves in different locations. To be serviced, each event requires that a robot with the appropriate skills comes to its location. We present two swarm-level solutions for guiding the navigation of the selected robots towards the events. We use a bio-inspired ad hoc network routing protocol to dynamically find and maintain paths between a robot and an event location in the mobile line-of-sight network, and use them to guide the robot to its goal. The performance of the two approaches is studied in a number of network scenarios presenting different density, mobility, and bandwidth availability.
Abstract. We study through simulation the performance of two MANET routing algorithms in a realistic urban environment. The two algorithms, AODV and AntHocNet, are representative of two different approaches and design methodologies. AODV is a a reference state-of-the-art algorithm following a purely reactive approach. AntHocNet is based on swarm intelligence and integrates proactive and reactive mechanisms. Our objective is to investigate the usefulness of the different approaches they adopt when confronted with the peculiarities of urban environments and the requirements of realworld applications. At this aim we define a detailed and realistic simulation setup. We model node mobility by limiting node movements to the streets and open spaces of the town, use a ray-tracing approach to model the propagation of radio waves, and investigate different kinds of realistic traffic patterns resulting from SMS messaging, VoIP communications, interaction between a control node and a fleet of vehicles, and existence of a fixed infrastructure mesh.
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