Ergodic Exploration of Distributed Information

Lauren M. Miller, Yonatan Silverman, Malcolm A. MacIver, Todd D. Murphey

Research output: Contribution to journalArticle

23 Scopus citations

Abstract

This paper presents an active search trajectory synthesis technique for autonomous mobile robots with nonlinear measurements and dynamics. The presented approach uses the ergodicity of a planned trajectory with respect to an expected information density map to close the loop during search. The ergodic control algorithm does not rely on discretization of the search or action spaces and is well posed for coverage with respect to the expected information density whether the information is diffuse or localized, thus trading off between exploration and exploitation in a single-objective function. As a demonstration, we use a robotic electrolocation platform to estimate location and size parameters describing static targets in an underwater environment. Our results demonstrate that the ergodic exploration of distributed information algorithm outperforms commonly used information-oriented controllers, particularly when distractions are present.

Original languageEnglish (US)
Article number7350162
Pages (from-to)36-52
Number of pages17
JournalIEEE Transactions on Robotics
Volume32
Issue number1
DOIs
StatePublished - Feb 1 2016

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Keywords

  • Biologically inspired robots
  • Search problems
  • information-driven sensor planning
  • motion control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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