Information-theoretic integration of sensing and communication for active robot networks

Frew, Eric W.

doi:10.4108/icst.robocomm2007.2203

Cited by 10 publications

(5 citation statements)

References 23 publications

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“…Other work concerns using a communication tether to link a ground, or base station, to an exploring agent [10], [11]. The paper [12] addresses the communication problem by integrating information theoretic measures into the objective function and demonstrates this approach on a chain configuration of mobile robots.…”

Section: A Related Workmentioning

confidence: 99%

Optimizing communication in air-ground robot networks using decentralized control

Gil¹,

Schwager²,

Julian³

et al. 2010

2010 IEEE International Conference on Robotics and Automation

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Abstract-We develop a distributed controller to position a team of aerial vehicles in a configuration that optimizes communication-link quality, to support a team of ground vehicles performing a collaborative task. We propose a gradientbased control approach where agents' positions locally minimize a physically motivated cost function. The contributions of this paper are threefold. We formulate of a cost function that incorporates a continuous, physical model of signal quality, SIR. We develop a non-smooth gradient-based controller that positions aerial vehicles to acheive optimized signal quality amongst all vehicles in the system. This controller is provably convergent while allowing for non-differentiability due to agents moving in or out of communication with one another. Lastly, we guarantee that given certain initial conditions or certain values of the control parameters, aerial vehicles will never disconnect the connectivity graph. We demonstrate our controller on hardware experiments using AscTec Hummingbird quadrotors and provide aggregate results over 10 trials. We also provide hardware-in-the-loop and MATALB simulation results, which demonstrate positioning of the aerial vehicles to minimize the cost function H and improve signal-quality amongst all communication links in the ground/air robot team.

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Section: A Related Workmentioning

confidence: 99%

Optimizing communication in air-ground robot networks using decentralized control

Gil¹,

Schwager²,

Julian³

et al. 2010

2010 IEEE International Conference on Robotics and Automation

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“…This is achieved by solving a convex optimization problem in an incremental fashion, however the extension to multiple robots moving to multiple desired points is not addressed. In [19], Frew presents an information-theoretic framework to integrate sensing and communication for planning of robot sensor networks. This approach takes uncertainty into account, however it is not clear if any type of connectivity guarantees can be made about the network.…”

Section: A Related Workmentioning

confidence: 99%

Mobile Heterogeneous Sensor Network for Prioritized Sensing

Cortez

Fierro²,

Wood³

2013

JCM

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Currently in the literature there does not exist a framework which incorporates a heterogeneous team of agents to solve the sensor network connectivity problem. An approach that makes use of a heterogeneous team of agents has several advantages when cost, integration of capabilities, or possible large search areas need to be investigated. A heterogeneous team allows for the robots to become "specialized" in their abilities and therefore accomplish sub-goals more efficiently which in turn makes the overall mission more efficient. In this paper we relax the assumption of network connectivity within the sensor network and introduce mobile communication relays to the network. This addition converts the homogeneous sensor network to a heterogeneous one. Based on the communication geometry of both sensing and communication relay agents we derive communication constraints within the network that guarantee network connectivity. We then define a heterogeneous proximity graph that encodes the communication links that exist within the heterogeneous network. By specifying particular edge weights in the proximity graph, we provide a technique for biasing particular connections within the heterogenous sensor network. Through a minimal spanning tree approach, we show how to minimize communication links within the network which allows for larger feasible motion sets of the sensing agents that guarantee the network remains connected. We also provide an algorithm that allows for adding communication links to the minimal spanning tree of the heterogeneous proximity graph to create a biconnected graph that is robust to a single node failure. We then combine a prioritized search algorithm and the communication constraints to provide a decentralized prioritized sensing control algorithm for a heterogenous sensor network that maintains network connectivity.

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“…In [4]- [6], Mostofi et al introduced communication-aware motion planning strategies, using an information-fusion approach, and considered the impact of distance-dependent path loss and fading on decentralized motion-planning and data fusion in mobile networks. An extension of [6], with a modification of the cost function, appeared in [7].…”

Section: Introductionmentioning

confidence: 99%

Communication-Aware Target Tracking using Navigation Functions – Centralized Case

Ghaffarkhah¹,

Mostofi²

2009

Proceedings of the 2nd International Conference on Robotic Communication and Coordination

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In this paper we consider a team of robots that are tasked with tracking a moving target cooperatively, while maintaining their connectivity to a base station and avoiding collision. We propose a novel extension of the classical navigation function framework in order to ensure task completion. More specifically, we modify the classical definition of th~.navigation functions to 1) incorporate measures of link qualities and 2) include the impact of a time-varying objective. Our proposed communication-aware navigation function framework is aimed at maintaining robot connectivity in realistic communication environments while avoiding collision with both fixed and moving ob-, . .stacles. We consider both packet-dropping and communlcatIonnoise based receivers. We furthermore prove the convergence of the proposed framework under certain conditions. Finally, our simulation results show the performance of the proposed navigation framework.

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Information-theoretic integration of sensing and communication for active robot networks

Cited by 10 publications

References 23 publications

Optimizing communication in air-ground robot networks using decentralized control

Optimizing communication in air-ground robot networks using decentralized control

Mobile Heterogeneous Sensor Network for Prioritized Sensing

Communication-Aware Target Tracking using Navigation Functions – Centralized Case

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