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A Study of human and receding horizon controller performance of a remote navigation task with obstacles and feedback delays

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Paladyn

Abstract

In this paper we present results from a study on the performance of humans and automatic controllers in a general remote navigation task. The remote navigation task is defined as driving a vehicle with nonholonomic kinematic constraints around obstacles toward a goal. We conducted experiments with humans and automatic controllers; in these experiments, the number and type of obstacles as well as the feedback delay was varied. Humans showed significantly more robust performance compared to that of a receding horizon controller. Using the human data, we then train a new human-like receding horizon controller which provides goal convergence when there is no uncertainty. We show that paths produced by the trained human-like controller are similar to human paths and that the trained controller improves robustness compared to the original receding horizon controller.

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Author information

Authors and Affiliations

  1. Department of Mechanical Science and Engineering at the University of Illinois, Urbana, Illinois, 61801, USA

    Chad R. Burns

  2. Department of Psychology at the University of Illinois, Champaign, Illinois, 61820, USA

    Ranxiao F. Wang

  3. Department of Industrial and Enterprise Engineering and Coordinated Science Laboratory at the University of Illinois, Urbana, Illinois, 61801, USA

    Dušan M. Stipanović

Authors
  1. Chad R. Burns
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  2. Ranxiao F. Wang
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  3. Dušan M. Stipanović
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Correspondence to Chad R. Burns.

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Burns, C.R., Wang, R.F. & Stipanović, D.M. A Study of human and receding horizon controller performance of a remote navigation task with obstacles and feedback delays. Paladyn 2, 44–63 (2011). https://doi.org/10.2478/s13230-011-0015-7

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  • DOI: https://doi.org/10.2478/s13230-011-0015-7

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