scholarly journals Ergodicity reveals assistance and learning from physical human-robot interaction

2019 ◽  
Vol 4 (29) ◽  
pp. eaav6079
Author(s):  
Kathleen Fitzsimons ◽  
Ana Maria Acosta ◽  
Julius P. A. Dewald ◽  
Todd D. Murphey
Keyword(s):  
Human Perception ◽  
Human Motion ◽  
Human Robot Interaction ◽  
The Body ◽  
Human Motion Analysis ◽  
Robotic Assistance ◽  
Information Channel ◽  
Neural Encoding ◽  
Robot Interaction ◽  
Information Theoretic

This paper applies information theoretic principles to the investigation of physical human-robot interaction. Drawing from the study of human perception and neural encoding, information theoretic approaches offer a perspective that enables quantitatively interpreting the body as an information channel and bodily motion as an information-carrying signal. We show that ergodicity, which can be interpreted as the degree to which a trajectory encodes information about a task, correctly predicts changes due to reduction of a person’s existing deficit or the addition of algorithmic assistance. The measure also captures changes from training with robotic assistance. Other common measures for assessment failed to capture at least one of these effects. This information-based interpretation of motion can be applied broadly, in the evaluation and design of human-machine interactions, in learning by demonstration paradigms, or in human motion analysis.

Modular control for human motion analysis and classification in human-robot interaction

2010 ◽  
Author(s):  
Juan Alberto Rivera-Bautista ◽  
Ana Cristina Ramirez-Hernandez ◽  
Virginia A. Garcia-Vega ◽  
Antonio Marin-Hernandez
Keyword(s):  
Motion Analysis ◽  
Human Motion ◽  
Human Robot Interaction ◽  
Human Motion Analysis ◽  
Robot Interaction ◽  
Modular Control

Modular control for human motion analysis and classification in Human-Robot interaction

2010 ◽  
Author(s):  
Juan Alberto Rivera-Bautista ◽  
Ana Cristina Ramirez-Hernandez ◽  
Virginia A. Garcia-Vega ◽  
Antonio Marin-Hernandez
Keyword(s):  
Motion Analysis ◽  
Human Motion ◽  
Human Robot Interaction ◽  
Human Motion Analysis ◽  
Robot Interaction ◽  
Modular Control

scholarly journals How does the robot feel? Perception of valence and arousal in emotional body language

2018 ◽  
Vol 9 (1) ◽  
pp. 168-182 ◽  
Author(s):  
Mina Marmpena ◽  
Angelica Lim ◽  
Torbjørn S. Dahl
Keyword(s):  
Human Perception ◽  
Ground Truth ◽  
Body Language ◽  
Human Robot Interaction ◽  
Behavioral Experiments ◽  
Robot Interaction ◽  
Expression Of Emotion ◽  
Exploratory Approach ◽  
Starting Point ◽  
Valence And Arousal

Abstract Human-robot interaction in social robotics applications could be greatly enhanced by robotic behaviors that incorporate emotional body language. Using as our starting point a set of pre-designed, emotion conveying animations that have been created by professional animators for the Pepper robot, we seek to explore how humans perceive their affect content, and to increase their usability by annotating them with reliable labels of valence and arousal, in a continuous interval space. We conducted an experiment with 20 participants who were presented with the animations and rated them in the two-dimensional affect space. An inter-rater reliability analysis was applied to support the aggregation of the ratings for deriving the final labels. The set of emotional body language animations with the labels of valence and arousal is available and can potentially be useful to other researchers as a ground truth for behavioral experiments on robotic expression of emotion, or for the automatic selection of robotic emotional behaviors with respect to valence and arousal. To further utilize the data we collected, we analyzed it with an exploratory approach and we present some interesting trends with regard to the human perception of Pepper’s emotional body language, that might be worth further investigation.

Socially Embodied Human-Robot Interaction

2015 ◽  
pp. 169-190 ◽  
Author(s):  
J. Lindblom ◽  
B. Alenljung
Keyword(s):  
User Experience ◽  
Human Robot Interaction ◽  
The Body ◽  
Human Interaction ◽  
Future Research ◽  
Crucial Importance ◽  
Robot Interaction ◽  
Use Of Technology ◽  
Fundamental Challenge ◽  
Socially Interactive Robots

A fundamental challenge of human interaction with socially interactive robots, compared to other interactive products, comes from them being embodied. The embodied nature of social robots questions to what degree humans can interact ‘naturally' with robots, and what impact the interaction quality has on the user experience (UX). UX is fundamentally about emotions that arise and form in humans through the use of technology in a particular situation. This chapter aims to contribute to the field of human-robot interaction (HRI) by addressing, in further detail, the role and relevance of embodied cognition for human social interaction, and consequently what role embodiment can play in HRI, especially for socially interactive robots. Furthermore, some challenges for socially embodied interaction between humans and socially interactive robots are outlined and possible directions for future research are presented. It is concluded that the body is of crucial importance in understanding emotion and cognition in general, and, in particular, for a positive user experience to emerge when interacting with socially interactive robots.

Determination of Variable Stiffness of a Human Elbow for Human-Robot Interaction

2014 ◽  
Author(s):  
Michael Boyarsky ◽  
Megan Heenan ◽  
Scott Beardsley ◽  
Philip Voglewede
Keyword(s):  
Experimental Data ◽  
Disturbance Rejection ◽  
Variable Stiffness ◽  
Important Variable ◽  
Human Motion ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Constant Stiffness ◽  
Stiffness Model ◽  
Motor Model

This paper aims to emulate human motion with a robot for the purpose of improving human-robot interaction (HRI). In order to engineer a robot that demonstrates functionally similar motion to humans, aspects of human motion such as variable stiffness must be captured. This paper successfully determined the variable stiffness humans use in the context of a 1 DOF disturbance rejection task by optimizing a time-varying stiffness parameter to experimental data in the context of a neuro-motor Simulink model. The significant improved agreement between the model and the experimental data in the disturbance rejection task after the addition of variable stiffness demonstrates how important variable stiffness is to creating a model of human motion. To enable a robot to emulate this motion, a predictive stiffness model was developed that attempts to reproduce the stiffness that a human would use in a given situation. The predictive stiffness model successfully decreases the error between the neuro-motor model and the experimental data when compared to the neuro-motor model with a constant stiffness value.

scholarly journals Human Motion Understanding for Selecting Action Timing in Collaborative Human-Robot Interaction

2019 ◽  
Vol 6 ◽  
Author(s):  
Francesco Rea ◽  
Alessia Vignolo ◽  
Alessandra Sciutti ◽  
Nicoletta Noceti
Keyword(s):  
Human Motion ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Action Timing

Multijoint passive elastic spine exoskeleton for stoop lifting assistance

2021 ◽  
Vol 18 (6) ◽  
pp. 172988142110620
Author(s):  
Jiyuan Song ◽  
Aibin Zhu ◽  
Yao Tu ◽  
Jiajun Zou
Keyword(s):  
Human Body ◽  
Musculoskeletal Diseases ◽  
Biomechanical Model ◽  
Human Robot Interaction ◽  
The Body ◽  
Robot Interaction ◽  
Load Bearing ◽  
High Stiffness ◽  
Wearable Robots ◽  
Natural Movement

In the task of carrying heavy objects, it is easy to cause back injuries and other musculoskeletal diseases. Although wearable robots are designed to reduce this danger, most existing exoskeletons use high-stiffness mechanisms, which are beneficial to load-bearing conduction, but this restricts the natural movement of the human body, thereby causing ergonomic risks. This article proposes a back exoskeleton composed of multiple elastic spherical hinges inspired by the biological spine. This spine exoskeleton can assist in the process of bending the body and ensure flexibility. We deduced the kinematics model of this mechanism and established an analytical biomechanical model of human–robot interaction. The mechanism of joint assistance of the spine exoskeleton was discussed, and experiments were conducted to verify the flexibility of the spine exoskeleton and the effectiveness of the assistance during bending.

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