Design and development of Nancy, a social robot

Abstract-In this paper, adaptive impedance control is proposed for a robot collaborating with a human partner, in the presence of unknown motion intention of the human partner and unknown robot dynamics. Human motion intention is defined as the desired trajectory in the limb model of the human partner, which is extremely difficult to obtain considering the nonlinear and time-varying property of the limb model. Neural networks are employed to cope with this problem, based on which an online estimation method is developed. The estimated motion intention is integrated into the developed adaptive impedance control, which makes the robot follow a given target impedance model. Under the proposed method, the robot is able to actively collaborate with its human partner, which is verified through experiment studies.

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“…The experiments are carried out on Nancy which is a humanoid introduced in [30] and shown in Fig. 3(a).…”

Section: Methodsmentioning

confidence: 99%

Human–Robot Collaboration Based on Motion Intention Estimation

2014

IEEE/ASME Trans. Mechatron.

267

131

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“…Robots are now being considered to be used in many applications (e.g. rehabilitation and elderly care) that require direct physical human-robot interaction [37,102].…”

Section: Introductionmentioning

confidence: 99%

Head Impact Severity Measures for Small Social Robots Thrown During Meltdown in Autism

Alhaddad

Cabibihan

Bonarini

2018

Int J of Soc Robotics

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Social robots have gained a lot of attention recently as they have been reported to be effective in supporting therapeutic services for children with autism. However, children with autism may exhibit a multitude of challenging behaviors that could be harmful to themselves and to others around them. Furthermore, social robots are meant to be companions and to elicit certain social behaviors. Hence, the presence of a social robot during the occurrence of challenging behaviors might increase any potential harm. In this paper, we identified harmful scenarios that might emanate between a child and a social robot due to the manifestation of challenging behaviors. We then quantified the harm levels based on severity indices for one of the challenging behaviors (i.e. throwing of objects). Our results showed that the overall harm levels based on the selected severity indices are relatively low compared to their respective thresholds. However, our investigation of harm due to throwing of a small social robot to the head revealed that it could potentially cause tissue injuries, subconcussive or even concussive events in extreme cases. The existence of such behaviors must be accounted for and considered when developing interactive social robots to be deployed for children with autism.

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“…In this section, the proposed method is examined on the robot Nancy which is developed in Social Robotics Laboratory, National University of Singapore [28]. Each joint of Nancy's arm is implemented using a cable-pulley transmission method which is achieved by a pull-pull configuration.…”

Section: Methodsmentioning

confidence: 99%

Force tracking control for motion synchronization in human-robot collaboration

2014

Robotica

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In this paper, motion synchronization is investigated for human-robot collaboration such that the robot is able to "actively" follow its human partner. Force tracking is achieved with the proposed method under the impedance control framework, subject to uncertain human limb dynamics. Adaptive control is developed to deal with point-to-point movement, and learning control and neural networks (NN) control are developed to generate periodic and arbitrary continuous trajectories, respectively. Stability and tracking performance of the closed-loop system are discussed through rigorous analysis. The validity of the proposed method is verified through simulation and experiment studies.

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Design and development of Nancy, a social robot

Cited by 18 publications

References 14 publications

Human–Robot Collaboration Based on Motion Intention Estimation

Human–Robot Collaboration Based on Motion Intention Estimation

Head Impact Severity Measures for Small Social Robots Thrown During Meltdown in Autism

Force tracking control for motion synchronization in human-robot collaboration

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