scholarly journals Evaluation of Calf Muscle Reflex Control in the ‘Ankle Strategy’ during Upright Standing Push-Recovery

2019 ◽  
Vol 9 (10) ◽  
pp. 2085 ◽  
Author(s):  
Muye Pang ◽  
Xiangui Xu ◽  
Biwei Tang ◽  
Kui Xiang ◽  
Zhaojie Ju

Revealing human internal control mechanisms during environmental interaction remains paramount and helpful in solving issues related to human-robot interaction. Muscle reflexes, which can directly and rapidly modify the dynamic behavior of joints, are the fundamental control loops of the Central Nervous System. This study investigates the calf muscle reflex control in the “ankle strategy” for human push-recovery movement. A time-increasing searching method is proposed to evaluate the feasibility of the reflex model in terms of predicting real muscle activations. Constraints with physiological implications are imposed to find the appropriate reflex gains. The experimental results show that the reflex model fits over 90% of the forepart of muscle activation. With the increasing of time, the Variance Accounted For (VAF) values drop to below 80% and reflex gains lose the physiology meaning. By dividing the muscle activation into two parts, the reflex formula is still workable for the rest part, with different gains and lower VAF values. This result may indicate that reflex control could more likely dominate the forepart of the push-recovery motion and an analogous control mechanism is still feasible for the rest of the motion part, with different gains. The proposed method provides an alternative way to obtain the human internal control mechanism desired for human-robot interaction task.

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5357 ◽  
Author(s):  
Yuqiang Wu ◽  
Fei Zhao ◽  
Wansoo Kim ◽  
Arash Ajoudani

In this work, we propose an intuitive and real-time model of the human arm active endpoint stiffness. In our model, the symmetric and positive-definite stiffness matrix is constructed through the eigendecomposition Kc=VDVT, where V is an orthonormal matrix whose columns are the normalized eigenvectors of Kc, and D is a diagonal matrix whose entries are the eigenvalues of Kc. In this formulation, we propose to construct V and D directly by exploiting the geometric information from a reduced human arm skeleton structure in 3D and from the assumption that human arm muscles work synergistically when co-contracted. Through the perturbation experiments across multiple subjects under different arm configurations and muscle activation states, we identified the model parameters and examined the modeling accuracy. In comparison to our previous models for predicting human active arm endpoint stiffness, the new model offers significant advantages such as fast identification and personalization due to its principled simplicity. The proposed model is suitable for applications such as teleoperation, human–robot interaction and collaboration, and human ergonomic assessments, where a personalizable and real-time human kinodynamic model is a crucial requirement.


2009 ◽  
Author(s):  
Matthew S. Prewett ◽  
Kristin N. Saboe ◽  
Ryan C. Johnson ◽  
Michael D. Coovert ◽  
Linda R. Elliott

2010 ◽  
Author(s):  
Eleanore Edson ◽  
Judith Lytle ◽  
Thomas McKenna

2020 ◽  
Author(s):  
Agnieszka Wykowska ◽  
Jairo Pérez-Osorio ◽  
Stefan Kopp

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.


2019 ◽  
Author(s):  
Cinzia Di Dio ◽  
Federico Manzi ◽  
Giulia Peretti ◽  
Angelo Cangelosi ◽  
Paul L. Harris ◽  
...  

Studying trust within human-robot interaction is of great importance given the social relevance of robotic agents in a variety of contexts. We investigated the acquisition, loss and restoration of trust when preschool and school-age children played with either a human or a humanoid robot in-vivo. The relationship between trust and the quality of attachment relationships, Theory of Mind, and executive function skills was also investigated. No differences were found in children’s trust in the play-partner as a function of agency (human or robot). Nevertheless, 3-years-olds showed a trend toward trusting the human more than the robot, while 7-years-olds displayed the reverse behavioral pattern, thus highlighting the developing interplay between affective and cognitive correlates of trust.


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