Abstract
In this paper, we consider clustered unmanned vehicle (UV) sensor networks for swarm sensing applications in a linear structure such as highway, tunnel, underwater pipelines, power lines, and international border. We assume that the linear UV sensor networks follow Thomas cluster process (TCP), in which the cluster locations are modelled by Poisson point process (PPP), while the cluster members (UVs) are normally distributed around their cluster centers. We focus on communications between UVs within a cluster such as local sensing data transfer or swarm coordination, where multiple UV pairs can share the same frequency band simultaneously. Thus, in the presence of co-channel interference both from the same cluster and the other clusters, we study the coverage and area spectral efficiency of the clustered UV sensor networks in a linear topology.
Highlights
Robotic systems have brought significant benefits to human lives over the past few decades [1].To extend the functional range of the robotic systems or to deploy them in unstructured environments, robotic technologies are integrated with communication technologies, fostering the emergence of networked robotics [2,3,4,5]
The channel is assumed to be quasi-static, where the network topology may vary over time, but the symbol duration is significantly smaller than the coherence time of the channel, meaning that the topology and fading channel remain the same over an entire symbol period. This assumption perhaps cannot be applied to highly mobile unmanned vehicle (UV) networks, but the system performance obtained under this assumption may be used as an upper bound on that of the UV network with high mobility since link reliability can be degraded by high mobility of nodes
The locations of the UVs in the 1D linear space are modelled by a Thomas cluster process (TCP), where the cluster centers follow a homogeneous Poisson point process (PPP) Φc with density λc
Summary
Robotic systems have brought significant benefits to human lives over the past few decades [1]. A team of networked robots can conduct search and rescue missions in extreme environments, such as the earthquake, exploring the unknown space, operating fast and accurate grasp of the real demand as highlighted in [6,7]. Unmanned vehicles (UVs), which can travel through a long pipe or tunnel-like systems, are useful for search and rescue applications in uncertain disaster environments such as chemical subway attack, nuclear explosion, and fire in pipelines. To explore these inaccessible environments, it is expected to organize swarms (clusters) of small unmanned ground, water, and airborne vehicles and launch complex missions that comprise several such teams [8]. Focusing on robust operation and cooperative sensing tasks in real time, UVs decompose and allocate tasks using onboard computation and inter-vehicle communication
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