Robust Estimation Using Context-Aware Filtering
Radoslav Ivanov, Nikolay A. Atanasov, Miroslav Pajic, George Pappas, Insup Lee

Citation
Radoslav Ivanov, Nikolay A. Atanasov, Miroslav Pajic, George Pappas, Insup Lee. "Robust Estimation Using Context-Aware Filtering". Allerton Conference on Communication, Control, and Computing, 2015.

Abstract
This paper presents the context-aware filter, an estimation technique that incorporates context measurements, in addition to the regular continuous measurements. Context measurements provide binary information about the system's context which is not directly encoded in the state; examples include a robot detecting a nearby building using image processing or a medical device alarming that a vital sign has exceeded a predefined threshold. These measurements can only be received from certain states and can therefore be modeled as a function of the system's current state. We focus on two classes of functions describing the probability of context detection given the current state; these functions capture a wide variety of detections that may occur in practice. We derive the corresponding context-aware filters, a Gaussian Mixture filter and another closed-form filter with a posterior distribution whose moments are derived in the paper. Finally, we evaluate the performance of both classes of functions through simulation of an unmanned ground vehicle.

Electronic downloads

Internal. This publication has been marked by the author for TerraSwarm-only distribution, so electronic downloads are not available without logging in.

Citation formats

• HTML

  Radoslav Ivanov, Nikolay A. Atanasov, Miroslav Pajic, George
  Pappas, Insup Lee. <a
  href="http://www.terraswarm.org/pubs/733.html"
  >Robust Estimation Using Context-Aware
  Filtering</a>, Allerton Conference on Communication,
  Control, and Computing, 2015.

• Plain text

  Radoslav Ivanov, Nikolay A. Atanasov, Miroslav Pajic, George
  Pappas, Insup Lee. "Robust Estimation Using
  Context-Aware Filtering". Allerton Conference on
  Communication, Control, and Computing, 2015.

• BibTeX

  @inproceedings{IvanovAtanasovPajicPappasLee15_RobustEstimationUsingContextAwareFiltering,
      author = {Radoslav Ivanov and Nikolay A. Atanasov and
                Miroslav Pajic and George Pappas and Insup Lee},
      title = {Robust Estimation Using Context-Aware Filtering},
      booktitle = {Allerton Conference on Communication, Control, and
                Computing},
      year = {2015},
      abstract = {This paper presents the context-aware filter, an
                estimation technique that incorporates context
                measurements, in addition to the regular
                continuous measurements. Context measurements
                provide binary information about the system's
                context which is not directly encoded in the
                state; examples include a robot detecting a nearby
                building using image processing or a medical
                device alarming that a vital sign has exceeded a
                predefined threshold. These measurements can only
                be received from certain states and can therefore
                be modeled as a function of the system's current
                state. We focus on two classes of functions
                describing the probability of context detection
                given the current state; these functions capture a
                wide variety of detections that may occur in
                practice. We derive the corresponding
                context-aware filters, a Gaussian Mixture filter
                and another closed-form filter with a posterior
                distribution whose moments are derived in the
                paper. Finally, we evaluate the performance of
                both classes of functions through simulation of an
                unmanned ground vehicle.},
      URL = {http://terraswarm.org/pubs/733.html}
  }
  

Posted by Nikolay A. Atanasov on 5 Feb 2016.
Groups: services