LQG framework explains performance of balancing inverted pendulum with incongruent visual feedback

Raz Leib, Justinas Cesonis, Sae Franklin, David W. Franklin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Successful manipulation of objects requires forming internal representations of the object dynamics. To do so, the sensorimotor system uses visual feedback of the object movement allowing us to estimate the object state and build the representation. One way to investigate this mechanism is by introducing a discrepancy between the visual feedback about the object's movement and the actual movement. This causes a decline in the ability to accurately control the object, shedding light about possible factors influencing the performance. In this study, we show that an optimal feedback control framework can account for the performance and kinematic characteristics of balancing an inverted pendulum when visual feedback of pendulum tip did not represent the actual pendulum tip. Our model suggests a possible mechanism for the role of visual feedback on forming internal representation of objects' dynamics.

Original languageEnglish
Title of host publication2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
PublisherInstitute of Electrical and Electronics Engineers
Pages1940-1943
Number of pages4
ISBN (Electronic)9781538613115
DOIs
StatePublished - 1 Jul 2019
Externally publishedYes
Event41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 - Berlin, Germany
Duration: 23 Jul 201927 Jul 2019

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Country/TerritoryGermany
CityBerlin
Period23/07/1927/07/19

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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