One-step-ahead kinematic compressive sensing
Author(s)Hover, Franz S.; Hummel, Robert; Mitra, Urbashi; Sukhatme, G.
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A large portion of work on compressive sampling and sensing has focused on reconstructions from a given measurement set. When the individual samples are expensive and optional, as is the case with autonomous agents operating in a physical domain and under specific energy limits, the CS problem takes on a new aspect because the projection is column-sparse, and the number of samples is not necessarily large. As a result, random sampling may no longer be the best tactic. The underlying incoherence properties in l0 reconstruction, however, can still motivate the purposeful design of samples in planning for CS with one or more agents; we develop here a greedy and computationally tractable sampling rule that will improve errors relative to random points. Several example cases illustrate that the approach is effective and robust.
DepartmentMassachusetts Institute of Technology. Department of Mechanical Engineering
Proceedings of the 2011 IEEE GLOBECOM Workshops (GC Wkshps)
Institute of Electrical and Electronics Engineers (IEEE)
Hover, Franz S. et al. “One-step-ahead Kinematic Compressive Sensing.” Proceedings of the 2011 IEEE GLOBECOM Workshops (GC Wkshps), 2011. 1314–1319.
Author's final manuscript