2013 IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems (2013)
Philadelphia, PA, USA USA
Sept. 9, 2013 to Sept. 13, 2013
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SASO.2013.37
In previous work, we introduced a novel swarming interpolation framework and validated its effectiveness on static fields. In this paper, we show that a slightly revised version of this framework is able to track fields that translate, rotate, or expand over time, enabling interpolation of both static and dynamic fields. Our framework can be used to control autonomous mobile sensors into flexible spatial arrangements in order to interpolate values of a field in an unknown region. The key advantage to this framework is that the stable sensor distribution can be chosen to resemble a Chebyshev distribution, which can be optimal for certain ideal geometries.
Robotics, Swarm Interpolation, Interpolation, Swarming, Swarm Intelligence, Sensor Networks, Control, Mobile Sensor Networks
J. Kirby, M. A. Oca, S. Senger, L. F. Rossi and C. Shen, "Tracking Time-Dependent Scalar Fields with Swarms of Mobile Sensors," 2013 IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems(SASO), Philadelphia, PA, USA USA, 2013, pp. 159-168.