scholarly journals On-the-Fly Detection of User Engagement Decrease in Spontaneous Human–Robot Interaction Using Recurrent and Deep Neural Networks

2019 ◽  
Vol 11 (5) ◽  
pp. 815-828
Author(s):  
Atef Ben-Youssef ◽  
Giovanna Varni ◽  
Slim Essid ◽  
Chloé Clavel
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Human Robot Interaction ◽  
User Engagement ◽  
Robot Interaction

scholarly journals A Brief Review of Neural Networks Based Learning and Control and Their Applications for Robots

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Yiming Jiang ◽  
Chenguang Yang ◽  
Jing Na ◽  
Guang Li ◽  
Yanan Li ◽  
...  
Keyword(s):  
Neural Networks ◽  
Nonlinear Systems ◽  
Human Robot Interaction ◽  
Learning Tools ◽  
Robot Interaction ◽  
Practical Applications ◽  
Powerful Learning ◽  
Wide Range ◽  
Complex Nonlinear Systems ◽  
And Control

As an imitation of the biological nervous systems, neural networks (NNs), which have been characterized as powerful learning tools, are employed in a wide range of applications, such as control of complex nonlinear systems, optimization, system identification, and patterns recognition. This article aims to bring a brief review of the state-of-the-art NNs for the complex nonlinear systems by summarizing recent progress of NNs in both theory and practical applications. Specifically, this survey also reviews a number of NN based robot control algorithms, including NN based manipulator control, NN based human-robot interaction, and NN based cognitive control.

Robot Agreeableness and User Engagement in Verbal Human-Robot Interaction

2020 ◽  
Author(s):  
Luca Garello ◽  
Francesco Grella ◽  
Stefano Castagnetta ◽  
Barbara Bruno ◽  
Carmine Tommaso Recchiuto ◽  
...  
Keyword(s):  
Human Robot Interaction ◽  
User Engagement ◽  
Robot Interaction

scholarly journals “Hmm, Did You Hear What I Just Said?”: Development of a Re-Engagement System for Socially Interactive Robots

Robotics ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 95
Author(s):  
Hoang-Long Cao ◽  
Paola Cecilia Torrico Moron ◽  
Pablo G. Esteban ◽  
Albert De Beir ◽  
Elahe Bagheri ◽  
...  
Keyword(s):  
Human Robot Interaction ◽  
Human Interaction ◽  
User Engagement ◽  
Affective States ◽  
Robot Interaction ◽  
Usability Test ◽  
Socially Interactive Robots ◽  
Technical Operation ◽  
Engagement System ◽  
Attention Level

Maintaining engagement is challenging in human–human interaction. When disengagements happen, people try to adapt their behavior with an expectation that engagement will be regained. In human–robot interaction, although socially interactive robots are engaging, people can easily drop engagement while interacting with robots. This paper proposes a multi-layer re-engagement system that applies different strategies through human-like verbal and non-verbal behaviors to regain user engagement, taking into account the user’s attention level and affective states. We conducted a usability test in a robot storytelling scenario to demonstrate technical operation of the system as well as to investigate how people react when interacting with a robot with re-engagement ability. Our usability test results reveal that the system has the potential to maintain a user’s engagement. Our selected users gave positive comments, through open-ended questions, to the robot with this ability. They also rated the robot with the re-engagement ability higher on several dimensions, i.e., animacy, likability, and perceived intelligence.

scholarly journals Context-Enhanced Human-Robot Interaction: Exploring the Role of System Interactivity and Multimodal Stimuli on the Engagement of People with Dementia

2021 ◽  
Author(s):  
Yuan Feng ◽  
Giulia Perugia ◽  
Suihuai Yu ◽  
Emilia I. Barakova ◽  
Jun Hu ◽  
...  
Keyword(s):  
Social Interaction ◽  
Rating Scales ◽  
Human Robot Interaction ◽  
Sufficient Evidence ◽  
Auditory Modality ◽  
User Engagement ◽  
Robot Interaction ◽  
People With Dementia ◽  
Tactile Stimuli

AbstractEngaging people with dementia (PWD) in meaningful activities is the key to promote their quality of life. Design towards a higher level of user engagement has been extensively studied within the human-computer interaction community, however, few extend to PWD. It is generally considered that increased richness of experiences can lead to enhanced engagement. Therefore, this paper explores the effects of rich interaction in terms of the role of system interactivity and multimodal stimuli by engaging participants in context-enhanced human-robot interaction activities. The interaction with a social robot was considered context-enhanced due to the additional responsive sensory feedback from an augmented reality display. A field study was conducted in a Dutch nursing home with 16 residents. The study followed a two by two mixed factorial design with one within-subject variable - multimodal stimuli - and one between-subject variable - system interactivity. A mixed method of video coding analysis and observational rating scales was adopted to assess user engagement comprehensively. Results disclose that when additional auditory modality was included besides the visual-tactile stimuli, participants had significantly higher scores on attitude, more positive behavioral engagement during activity, and a higher percentage of communications displayed. The multimodal stimuli also promoted social interaction between participants and the facilitator. The findings provide sufficient evidence regarding the significant role of multimodal stimuli in promoting PWD’s engagement, which could be potentially used as a motivation strategy in future research to improve emotional aspects of activity-related engagement and social interaction with the human partner.

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