Ergodic exploration with stochastic sensor dynamics

Gerardo De La Torre, Kathrin Flaßkamp, Ahalya Prabhakar, Todd D. Murphey

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

5 Scopus citations


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.
Number of pages6
ISBN (Electronic)9781467386821
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
ISSN (Print)0743-1619


Other2016 American Control Conference, ACC 2016
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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