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Technology Reviews

Tools and Techniques for Mobile Sensor Network Control

[+] Author and Article Information
J. Karl Hedrick

Center for Collaborative Control of Unmanned Vehicles, University of California, Berkeley, Berkeley, CA 94720khedrick@me.berkeley.edu

Brandon Basso1

Center for Collaborative Control of Unmanned Vehicles, University of California, Berkeley, Berkeley, CA 94720bbasso@berkeley.edu

Joshua Love

Center for Collaborative Control of Unmanned Vehicles, University of California, Berkeley, Berkeley, CA 94720jlove@me.berkeley.edu

Benjamin M. Lavis

Center for Collaborative Control of Unmanned Vehicles, University of California, Berkeley, Berkeley, CA 94720b.lavis@berkeley.edu

1

Corresponding author.

J. Dyn. Sys., Meas., Control 133(2), 024001 (Feb 28, 2011) (7 pages) doi:10.1115/1.4003369 History: Received July 19, 2009; Revised October 26, 2010; Published February 28, 2011; Online February 28, 2011

This paper compares some of the common tools and techniques that enable state-of-the-art systems to provide high-level control of mobile sensor networks. There is currently a great deal of interest in employing unmanned and autonomous vehicles in intelligence, surveillance, and reconnaissance operations. Although this paper addresses issues common to all mobile sensor networks, the applications presented are typically associated with autonomous vehicles. We focus specifically on three high-level areas: 1. mission definition languages that allow human users to compose missions defined in terms of tasks, 2. communication-addressing degradation and loss and relationship to underlying system architecture design, and 3. task allocation among the assets.

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Copyright © 2011 by American Society of Mechanical Engineers
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References

Figures

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Figure 2

Sequential composition in a CSL Petri net

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Figure 3

Berkeley’s mobile sensor network architecture, from Ref. 17

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Figure 4

A generic MSN in which multiple users (U) want to access information on multiple platforms (P), running possibly different operating systems (OS), with applications written in different languages (L)

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Figure 5

The Berkeley-Sydney DARPA grand challenge team top-level system diagram. Software components are shown distributed across multiple computing hosts (43).

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Figure 6

System diagram for a MSN with multiple platforms, hosts, and users

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Figure 7

Overview of several RSS projects

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