Algorithms for Robotic Deployment of WSN in Adaptive Sampling Applications

  • Dan O. Popa
  • Frank L. Lewis
Part of the Signals and Communication Technology book series (SCT)

Recently, there has been renewed interest in using mobile robots as sensor-carrying platforms in order to perform hazardous tasks, such as searching for harmful biological and chemical agents, search and rescue in disaster areas, or environmental mapping and monitoring. Even though mobility introduces additional degrees of complexity in managing an untethered collection of sensors, it also expands the coverage and fault tolerance of a sensor network. When considering mobile sensor nodes, many important issues regarding the deployment architecture have yet to be fully addressed, including trade-offs between node size, cost, and coverage, the selection of appropriate information measures to quantify the data collection performance of the mobile wireless sensor network (MWSN), distribution of communication and computation, etc.

Developing robust deployment algorithms for mobile sensor units requires simultaneous consideration of several optimization problems that have traditionally been addressed separately. One problem is related to the quality and usefulness of the collected sensor information (e.g., choosing optimal locations in space where environmental samples are taken by the robotic system), another is related to the robot team behavior for goal attainment (e.g., how does the robot team accomplish the sampling objectives), and a third is related to routing and congestion control in the ad-hoc wireless network formed by the robots (e.g., how do we reposition the robots to increase the communication bandwidth).


Sensor Network Sensor Node Mobile Robot Extended Kalman Filter Congestion Control 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Dan O. Popa
    • 1
  • Frank L. Lewis
    • 1
  1. 1.Automation and Robotics Research InstituteUniversity of Texas at ArlingtonArlingtonUSA

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