A Comprehensive Overview and Characterization of Wireless Channels for Networked Robotic and Control Systems

2014

ACM Trans. Sen. Netw.

Self Cite

In this paper, we study the problem of dynamic coverage of a set of points of interest (POIs) in a time-varying environment. We consider the scenario where a physical quantity is constantly growing at certain rates at the POIs. A number of mobile agents are then deployed to periodically cover (sense or service) the POIs and keep the physical quantity under control bounded at all the POIs. We assume a communication-constrained operation, where the mobile agents need to communicate to a fixed remote station over realistic wireless links to complete their coverage task. We then propose novel mixed-integer linear programs (MILPs) to design periodic trajectories and TX power policies for the mobile agents that minimize the total energy (the summation of motion and communication energy) consumption of the mobile agents in each period, while 1) guaranteeing the boundedness of the quantity of interest at all the POIs, and 2) meeting the constraints on the connectivity of the mobile agents, the frequency of covering the POIs, and the total energy budget of the mobile agents. We furthermore provide a probabilistic analysis of the problem. Our results show the superior performance of the proposed framework for dynamic coverage in realistic fading environments.

Section: Simulation Resultsmentioning

confidence: 99%

Section: Snrthn0bmentioning

confidence: 99%

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Dynamic Networked Coverage of Time-Varying Environments in the Presence of Fading Communication Channels

Ghaffarkhah

2014

ACM Trans. Sen. Netw.

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“…The channel in the workspace is generated with the following real channel parameters from downtown San Francisco [27]: path loss exponent is 4.57, standard deviation of shadowing is 4, decorrelation distance of shadowing is 3.52 m, and the multipath fading is Rician fading with Rician parameter of 5.9. The channel is extended to populate the space of interest using our probabilistic channel simulator [28]. We assume that the robots have 5% a priori channel samples gathered in the same environment.…”

Section: Simulation Resultsmentioning

confidence: 99%

Efficient communication-aware dynamic coverage using space-filling curves

Yuan

2014 American Control Conference

2014

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Abstract-In this paper, we consider a dynamic coverage problem where a team of mobile robots needs to cover a set of time-varying Points of Interest (POIs), while maintaining their connectivity to a remote station in a realistic communication environment. Our goal is to design the motion and communication strategies of the robots such that they periodically visit the POIs, communicate the gathered information to a remote station, minimize their total energy costs, including motion, sensing and communication energy, and satisfy other system constraints. In our previous work [1], we have shown how to pose this problem as a Mixed Integer Linear Program (MILP), which is computationally expensive. In this paper, we focus on designing a considerably more computationally-efficient heuristic approach to tackle this problem. More specifically, we propose to utilize the space-filling curves to efficiently assign the POIs and plan the trajectories of the robots. Under certain conditions, we mathematically show that our heuristic approach is at most a constant factor away from the global optimum. Our simulation results then confirm that our approach is considerably faster than solving the MILP, especially when the dimension of the problem is high. They further show that the energy consumption of our approach is only around 26% more than the optimum.

“…There are two key enabling factors that contribute to the success of our experimental setup: 1) use of robotic units, which enables automated positioning for collecting wireless measurements and 2) use of adaptive directional narrow-beam antennas. The latter is crucial in limiting the impact of multipath fading, as we showed in [35]. As can be seen from (3), our mapping framework is based on following the shadowing component.…”

Section: A Summary Of the Enabling Experimental Platformmentioning

confidence: 99%

Cooperative Wireless-Based Obstacle/Object Mapping and See-Through Capabilities in Robotic Networks

IEEE Trans. on Mobile Comput.

2013

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Abstract-In this paper, we develop a theoretical and experimental framework for the mapping of obstacles (including occluded ones), in a robotic cooperative network, based on a small number of wireless channel measurements. This would allow the robots to map an area before entering it. We consider three approaches based on coordinated space, random space, and frequency sampling, and show how the robots can exploit the sparse representation of the map in space, wavelet or spatial variations, in order to build it with minimal sensing. We then show the underlying tradeoffs of all the possible sampling, sparsity and reconstruction techniques. Our simulation and experimental results show the feasibility and performance of the proposed framework. More specifically, using our experimental robotic platform, we show preliminary results in successfully mapping a number of real obstacles and having see-through capabilities with real structures, despite the practical challenges presented by multipath fading.