Development of a Handshake Robot System for Embodied Interaction with Humans

Jindai, Mitsuru; Watanabe, Tetsu; Shibata, Satoru; Yamamoto, Takakazu

doi:10.1109/roman.2006.314484

Cited by 17 publications

(29 citation statements)

References 6 publications

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“…Nevertheless, in several studies a telerobotic interface was used for exploring handshakes [6][7][8][9][10][11] and other forms of human-human interaction 12 . In addition, in this version of the test, we didn't consider the duration of the handshake, the initiation and release times, its multi-dimensional nature and the hand trajectories before and after the physical contact.…”

Section: Discussionmentioning

confidence: 99%

One Dimensional Turing-Like Handshake Test for Motor Intelligence

Karniel

Avraham

Peles

et al. 2010

JoVE

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In the Turing test, a computer model is deemed to "think intelligently" if it can generate answers that are not distinguishable from those of a human. However, this test is limited to the linguistic aspects of machine intelligence. A salient function of the brain is the control of movement, and the movement of the human hand is a sophisticated demonstration of this function. Therefore, we propose a Turing-like handshake test, for machine motor intelligence. We administer the test through a telerobotic system in which the interrogator is engaged in a task of holding a robotic stylus and interacting with another party (human or artificial). Instead of asking the interrogator whether the other party is a person or a computer program, we employ a two-alternative forced choice method and ask which of two systems is more human-like. We extract a quantitative grade for each model according to its resemblance to the human handshake motion and name it "Model Human-Likeness Grade" (MHLG). We present three methods to estimate the MHLG. (i) By calculating the proportion of subjects' answers that the model is more human-like than the human; (ii) By comparing two weighted sums of human and model handshakes we fit a psychometric curve and extract the point of subjective equality (PSE); (iii) By comparing a given model with a weighted sum of human and random signal, we fit a psychometric curve to the answers of the interrogator and extract the PSE for the weight of the human in the weighted sum. Altogether, we provide a protocol to test computational models of the human handshake. We believe that building a model is a necessary step in understanding any phenomenon and, in this case, in understanding the neural mechanisms responsible for the generation of the human handshake. Video LinkThe video component of this article can be found at

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Section: Discussionmentioning

confidence: 99%

One Dimensional Turing-Like Handshake Test for Motor Intelligence

Karniel

Avraham

Peles

et al. 2010

JoVE

View full text Add to dashboard Cite

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“…To achieve a successful handshaking, both participants have to be synchronized. It is believed that this synchronization of the embodied rhythms, establishes an accepted relationship and a feeling of safety [1].…”

Section: Introductionmentioning

confidence: 99%

“…Previous works have discussed solutions for each of the phases above, but synchronization during the shake-motion is a more discussed issue. For the first phase an approaching motion is proposed under the assumption that the human is always the requester and the robot is the respondent [1], [2], [3]. The approach in [1], [2], [3] is heavily based on vision in order to acquire online the human arm configuration trajectory and produce its mirror with a delay for the robot.…”

Section: Introductionmentioning

confidence: 99%

A kinematic controller for human-robot handshaking using internal motion adaptation

Papageorgiou

Doulgeri

2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

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This work proposes a kinematic control method for human-robot handshake motions achieving fast motion synchronization given a preset internal robot handshake motion and a compliance level that reflects the robot's level of passiveness. The proposed method combines a non-linear dynamic system having an attractive limit cycle with an admittance controller and an adaptation mechanism so that interaction forces are minimized and a consensus oscillation is achieved between the engaging participants. The proposed method is validated by experimenting with a KUKA LWR4+ 7dof arm under various scenarios.

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“…The telerobotic interface is necessary to grant the human-computer discrimination significance, much as the teletype was necessary to hide the computer from the questioning human in the original Turing test. Handshaking has been discussed in the social context [4,5] but the development of artificial handshake systems is still in its infancy [6][7][8][9][10]. Nevertheless, research of human motor control has generated many theories as to the nature of hand movements, and the proposed Turing-like handshake test can be useful in identifying the aspects of these theories that are essential for producing a human-like handshake movement.…”

Section: Introductionmentioning

confidence: 99%

A Turing-Like Handshake Test for Motor Intelligence

Karniel

Nisky

Avraham

et al. 2010

Haptics: Generating and Perceiving Tangible Sensations

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Abstract. In the Turing test, a computer model is deemed to "think intelligently" if it can generate answers that are not distinguishable from those of a human. This test is limited to the linguistic aspects of machine intelligence. A salient function of the brain is the control of movement, with the human hand movement being a sophisticated demonstration of this function. Therefore, we propose a Turing-like handshake test, for machine motor intelligence. We administer the test through a telerobotic system in which the interrogator is engaged in a task of holding a robotic stylus and interacting with another party (human, artificial, or a linear combination of the two). Instead of asking the interrogator whether the other party is a person or a computer program, we employ a forced-choice method and ask which of two systems is more humanlike. By comparing a given model with a weighted sum of human and artificial systems, we fit a psychometric curve to the answers of the interrogator and extract a quantitative measure for the computer model in terms of similarity to the human handshake.

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Development of a Handshake Robot System for Embodied Interaction with Humans

Cited by 17 publications

References 6 publications

One Dimensional Turing-Like Handshake Test for Motor Intelligence

One Dimensional Turing-Like Handshake Test for Motor Intelligence

A kinematic controller for human-robot handshaking using internal motion adaptation

A Turing-Like Handshake Test for Motor Intelligence

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