Analysis of Human Skill Development in Manual Ramp-Tracking Tasks

M. Willems, D. M. Pool, K. Van Der El, H. J. Damveld, M. M. Van Paassen, Max Mulder

Research output: Contribution to journalConference articleScientificpeer-review

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Abstract

Human modelling approaches are typically limited to feedback-only, compensatory tracking tasks. Advances in system identification techniques allow us to consider more realistic tasks that involve feedforward and even precognitive control. In this paper we study the human development of a feedforward control response while learning to accurately follow a ramp-shaped target signal in the presence of a disturbance acting on the controlled element. An experiment was conducted in which two groups of eight subjects each tracked ramps of different steepnesses in a random or ordered fashion. In addition, ordered runs were followed by a 'surprise' run with a random ramp steepness. Results show that operators learn rapidly, continue to learn during the entire experiment, and can adapt very quickly to surprise situations. Experiments involving learning operators are challenging, as it is difficult to balance-out all experimental conditions and control for inevitable differences between (groups of) subjects.

Original languageEnglish
Pages (from-to)235-240
Number of pages6
JournalIFAC-PapersOnline
Volume52
Issue number19
DOIs
Publication statusPublished - 2019
Event14th IFAC Symposium on Analysis, Design, and Evaluation of Human Machine Systems, HMS 2019 - Tallinn, Estonia
Duration: 16 Sept 201919 Sept 2019

Keywords

  • cybernetics
  • learning
  • manual control
  • modeling
  • skill

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