English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Identifying Time-Varying Pilot Responses: A Regularized Recursive Least-Squares Algorithm

Olivari, M., Venrooij, J., Nieuwenhuizen, F., Pollini, L., & Bülthoff, H. (2016). Identifying Time-Varying Pilot Responses: A Regularized Recursive Least-Squares Algorithm. In AIAA Modeling and Simulation Technologies Conference: Held at the AIAA SciTech Forum 2016 (pp. 385-399). Red Hook, NY, USA: Curran.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/21.11116/0000-0000-7AAA-8 Version Permalink: http://hdl.handle.net/21.11116/0000-0000-7AAB-7
Genre: Conference Paper

Files

show Files

Locators

show
hide
Locator:
Link (Any fulltext)
Description:
-

Creators

show
hide
 Creators:
Olivari, M1, 2, 3, 4, Author              
Venrooij, J2, Author              
Nieuwenhuizen, FM2, Author              
Pollini, L, Author
Bülthoff, HH1, 2, 3, Author              
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
3Project group: Cybernetics Approach to Perception & Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528701              
4Project group: Motion Perception & Simulation, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528705              

Content

show
hide
Free keywords: -
 Abstract: Methods for identifying pilot's responses commonly assume time-invariant dynamics. However, humans are likely to vary their responses during realistic control scenarios. In this work an identification method is developed for estimating time-varying responses to visual and force feedback during a compensatory tracking task. The method describes pilot's responses with finite impulse response filters and use a Regularized Recursive Least Squares (RegRLS) algorithm to simultaneously estimate filter coefficients. The method was validated in a Monte-Carlo simulation study with different levels of remnant noise. With low levels of remnant noise, estimates were accurate and tracked the time-varying behaviour of the simulated responses. On the other hand, estimates showed high variability in case of large remnant noise. However, parameters of the RegRLS could be further optimized to improve robustness to large remnant noise. Taken together, these findings suggest that the novel RegRLS algorithm could be used to estimate time-varying pilot's responses in real human-in-the-loop experiments.

Details

show
hide
Language(s):
 Dates: 2016-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.2514/6.2016-1182
BibTex Citekey: OlivariVNPB2016
 Degree: -

Event

show
hide
Title: AIAA Modeling and Simulation Technologies Conference: Held at the AIAA SciTech Forum 2016
Place of Event: San Diego, CA, USA
Start-/End Date: -

Legal Case

show

Project information

show

Source 1

show
hide
Title: AIAA Modeling and Simulation Technologies Conference: Held at the AIAA SciTech Forum 2016
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Red Hook, NY, USA : Curran
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 385 - 399 Identifier: ISBN: 978-1-5108-2065-4