Pseudo-Haptic Feedback in Teleoperation.
Identifieur interne : 000029 ( PubMed/Corpus ); précédent : 000028; suivant : 000030Pseudo-Haptic Feedback in Teleoperation.
Auteurs : Carsten Neupert ; Sebastian Matich ; Nick Scherping ; Mario Kupnik ; Roland Werthschutzky ; Christian HatzfeldSource :
- IEEE transactions on haptics [ 2329-4051 ] ; 2016.
Abstract
In this paper, we develop possible realizations of pseudo-haptic feedback in teleoperation systems based on existing works for pseudo-haptic feedback in virtual reality and the intended applications. We derive four potential factors affecting the performance of haptic feedback (calculation operator, maximum displacement, offset force, scaling factor), which are analyzed in three compliance identification experiments. First, we analyze the principle usability of pseudo-haptic feedback by comparing information transfer measures for teleoperation and direct interaction. Pseudo-haptic interaction yields well above-chance performance, while direct interaction performs almost perfectly. In order to optimize pseudo-haptic feedback, in the second study we perform a full-factorial experimental design with 36 subjects performing 6480 trials with 36 different treatments. Information transfer ranges from 0.68 bit to 1.72 bit in a task with a theoretical maximum of 2.6 bit, with a predominant effect of the calculation operator and a minor effect of the maximum displacement. In a third study, short- and long-term learning effects are analyzed. Learning effects regarding the performance of pseudo-haptic feedback cannot be observed for single-day experiments. Tests over ten days show a maximum increase in information transfer of 0.8 bit. The results show the feasibility of pseudo-haptic feedback for teleoperation and can be used as design basis for task-specific systems.
DOI: 10.1109/TOH.2016.2557331
PubMed: 27116752
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pubmed:27116752Le document en format XML
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<front><div type="abstract" xml:lang="en">In this paper, we develop possible realizations of pseudo-haptic feedback in teleoperation systems based on existing works for pseudo-haptic feedback in virtual reality and the intended applications. We derive four potential factors affecting the performance of haptic feedback (calculation operator, maximum displacement, offset force, scaling factor), which are analyzed in three compliance identification experiments. First, we analyze the principle usability of pseudo-haptic feedback by comparing information transfer measures for teleoperation and direct interaction. Pseudo-haptic interaction yields well above-chance performance, while direct interaction performs almost perfectly. In order to optimize pseudo-haptic feedback, in the second study we perform a full-factorial experimental design with 36 subjects performing 6480 trials with 36 different treatments. Information transfer ranges from 0.68 bit to 1.72 bit in a task with a theoretical maximum of 2.6 bit, with a predominant effect of the calculation operator and a minor effect of the maximum displacement. In a third study, short- and long-term learning effects are analyzed. Learning effects regarding the performance of pseudo-haptic feedback cannot be observed for single-day experiments. Tests over ten days show a maximum increase in information transfer of 0.8 bit. The results show the feasibility of pseudo-haptic feedback for teleoperation and can be used as design basis for task-specific systems.</div>
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<Abstract><AbstractText NlmCategory="UNASSIGNED">In this paper, we develop possible realizations of pseudo-haptic feedback in teleoperation systems based on existing works for pseudo-haptic feedback in virtual reality and the intended applications. We derive four potential factors affecting the performance of haptic feedback (calculation operator, maximum displacement, offset force, scaling factor), which are analyzed in three compliance identification experiments. First, we analyze the principle usability of pseudo-haptic feedback by comparing information transfer measures for teleoperation and direct interaction. Pseudo-haptic interaction yields well above-chance performance, while direct interaction performs almost perfectly. In order to optimize pseudo-haptic feedback, in the second study we perform a full-factorial experimental design with 36 subjects performing 6480 trials with 36 different treatments. Information transfer ranges from 0.68 bit to 1.72 bit in a task with a theoretical maximum of 2.6 bit, with a predominant effect of the calculation operator and a minor effect of the maximum displacement. In a third study, short- and long-term learning effects are analyzed. Learning effects regarding the performance of pseudo-haptic feedback cannot be observed for single-day experiments. Tests over ten days show a maximum increase in information transfer of 0.8 bit. The results show the feasibility of pseudo-haptic feedback for teleoperation and can be used as design basis for task-specific systems.</AbstractText>
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