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Minimum jerk based ...
Minimum jerk based prediction of user actions for a ball catching task
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- Bratt, Mattias (författare)
- KTH,Centrum för Autonoma System, CAS
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- Smith, Christian (författare)
- KTH,Centrum för Autonoma System, CAS
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- Christensen, Henrik I. (författare)
- KTH,Centrum för Autonoma System, CAS
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(creator_code:org_t)
- IEEE conference proceedings, 2007
- 2007
- Engelska.
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Ingår i: IEEE International Conference on Intelligent Robots and Systems. - : IEEE conference proceedings. - 9781424409112 ; , s. 2716-2722
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Abstract
Ämnesord
Stäng
- The present paper examines minimum jerk models for human kinematics as a tool to predict user input in teleoperation with significant dynamics. Predictions of user input can be a powerful tool to bridge time-delays and to trigger autonomous sub-sequences. In this paper an example implementation is presented, along with the results of a pilot experiment in which a virtual reality simulation of a teleoperated ball-catching scenario is used to test the predictive power of the model. The results show that delays up to 100 ms can potentially be bridged with this approach.
Nyckelord
- prediction
- minimum jerk
- teleoperation
- TECHNOLOGY
- TEKNIKVETENSKAP
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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