An experimental study on the role of touch in shared virtual environments
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HCI International '97 Proceedings of the Seventh International Conference on Human-Computer Interaction-Volume 1 - Volume I
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Presence: Teleoperators and Virtual Environments
Presence: Teleoperators and Virtual Environments
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IEEE Transactions on Haptics
Homotopy switching model for dyad haptic interaction in physical collaborative tasks
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ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
A turing-like handshake test for motor intelligence
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Three alternatives to measure the human-likeness of a handshake model in a turing-like test
Presence: Teleoperators and Virtual Environments
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In the past, working spaces of humans and robots were strictly separated, but recent developments have sought to bring robots into closer interaction with humans. In this context, physical human-robot interaction represents a major challenge, as it is based on continuous bilateral information and energy exchanges which result in a mutual adaptation of the partners. To address the challenge of designing robot collaboration partners, making them as human-like as possible is an approach often adopted. In order to compare different implementations with each other, their degree of human-likeness on a continuous scale is required. So far, the human-likeness of haptic interaction partners has only been studied in the form of binary choices. In this paper, we first introduce methods that allow measuring the human-likeness of haptic interaction partners on a continuous scale. In doing so, two subjective rating methods are proposed and correlated with a task performance measure. To demonstrate the applicability and validity of the proposed measures, they are applied to a joint kinesthetic manipulation task and used to compare two different implementations of a haptic interaction partner: a feedforward model based on force replay, and a feedback model. This experiment demonstrates the use of the proposed measures in building a continuous human-likeness scale and the interpretation of the scale values achieved for formulating guidelines for future robot implementations.