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Operator matching during visually aided teleoperation

Abstract:
Two contrasting models are proposed to account for an operator's performance during an insertion task using a teleoperated robot arm in which, in addition to haptic feedback, visual guidance is provided via a computer-generated display of the workspace. In the first model, the operator's internal aim is formulated as one of maximising the amount of information available, and in the second as one of minimising variance. Experimental measurements of the times to complete such a task are made, with various degrees of noise added to the pose of objects and different smoothing applied before generating the display. The observations appear inconsistent with the first performance model, suggesting that the operator prefers to use partial information rapidly, rather than to suffer the delay associated with extracting full information. The observations are more consistent with the operator as a minimiser of variance, an idea used successfully (albeit embodied in a different controller) by others in the modelling of human eye and arm trajectories, and in the prediction of the empirical Fitts' law found in reaching and touching tasks. It is found that under relatively high noise, the operator performs best when pose is low-pass-filtered with a cut-off frequency comparable with the natural frequency at which the operator interacts with the environment. © 2004 Elsevier B.V. All rights reserved.
Publication status:
Published

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Publisher copy:
10.1016/j.robot.2004.10.003

Authors

More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author


Journal:
ROBOTICS AND AUTONOMOUS SYSTEMS More from this journal
Volume:
50
Issue:
1
Pages:
69-80
Publication date:
2005-01-31
DOI:
ISSN:
0921-8890


Language:
English
Keywords:
Pubs id:
pubs:318090
UUID:
uuid:0c7e9454-166b-4ce4-9221-28d1ad738621
Local pid:
pubs:318090
Source identifiers:
318090
Deposit date:
2012-12-19
ARK identifier:

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