Ergodic exploration with stochastic sensor dynamics

Gerardo De La Torre, Kathrin Flaßkamp, Ahalya Prabhakar, Todd David Murphey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Ergodic exploration has been shown to be an effective framework for autonomous sensing and exploration. The objective of ergodic control is to minimize the difference between the distribution of the time-averaged sensor trajectory and a spatial probability distribution function representing information density. Therefore, the time a sensor spends sampling a particular region is manipulated to correspond to the anticipated information density of that region. This paper introduces a trajectory optimization approach for ergodic exploration in the presence of stochastic sensor dynamics. The stochastic differential dynamic programming algorithm is formulated in the context of ergodic exploration. Numerical studies demonstrate the proposed framework's ability to mitigate stochastic effects.

Original languageEnglish (US)
Title of host publication2016 American Control Conference, ACC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2971-2976
Number of pages6
ISBN (Electronic)9781467386821
DOIs
StatePublished - Jul 28 2016
Event2016 American Control Conference, ACC 2016 - Boston, United States
Duration: Jul 6 2016Jul 8 2016

Publication series

NameProceedings of the American Control Conference
Volume2016-July
ISSN (Print)0743-1619

Other

Other2016 American Control Conference, ACC 2016
CountryUnited States
CityBoston
Period7/6/167/8/16

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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    De La Torre, G., Flaßkamp, K., Prabhakar, A., & Murphey, T. D. (2016). Ergodic exploration with stochastic sensor dynamics. In 2016 American Control Conference, ACC 2016 (pp. 2971-2976). [7525371] (Proceedings of the American Control Conference; Vol. 2016-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2016.7525371