Trajectory optimization for continuous ergodic exploration

Lauren M. Miller, Todd D. Murphey

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

34 Scopus citations


An algorithm is presented for generating trajectories for efficient exploration that takes into account a probabilistic representation of information density over a sampling region. The problem is cast as a continuous-time trajectory optimization problem, where the objective function directly involves the relationship between the probability density functions representing the spatial distribution and the statistical representation of the time-averaged trajectory. The difference is expressed using ergodicity. It is shown that the trajectory optimization problem can be solved using descent directions that are solutions to linear quadratic optimal control problems. The proposed method generates continuous-time optimal feedback controllers, demonstrated in simulation for a nonlinear sensor model.

Original languageEnglish (US)
Title of host publication2013 American Control Conference, ACC 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Print)9781479901777
StatePublished - Jan 1 2013
Event2013 1st American Control Conference, ACC 2013 - Washington, DC, United States
Duration: Jun 17 2013Jun 19 2013

Publication series

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


Other2013 1st American Control Conference, ACC 2013
Country/TerritoryUnited States
CityWashington, DC

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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