2P1-N-029 Estimating human emotion with EEG for human-robot interaction(Emotion, Sensitivity, and Embodiment 2,Mega-Integration in Robotics and Mechatronics to Assist Our Daily Lives)

In our daily lives, we need to predict and understand others’ behaviour in order to navigate through our social environment. Predictions concerning other humans’ behaviour usually refer to their mental states, such as beliefs or intentions. Such a predictive strategy is called adoption of the intentional stance. In this paper, we review literature related to the concept of intentional stance from the perspectives of philosophy, psychology, human development, culture and human-robot interaction. We propose that adopting the intentional stance might be a central factor in facilitating social attunement with artificial agents. The paper first reviews the theoretical considerations regarding the intentional stance, and examines literature related to the development of intentional stance across the life span. Subsequently, it discusses cultural norms as grounded in the intentional stance and finally, it focuses on the issue of adopting the intentional stance towards artificial agents, such as humanoid robots. At the dawn of the artificial intelligence era, the question of how (and when) we predict and explain robots’ behaviour by referring to mental states is of high interest. The paper concludes with the discussion of the ethical consequences of robots towards which we adopt the intentional stance, and sketches future directions in research on this topic.

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Allocentric Emotional Affordances in HRI: The Multimodal Binding

10.20944/preprints201808.0312.v1 ◽

2018 ◽

Author(s):

Jordi Vallverdú ◽

Gabriele Trovato ◽

Lorenzo Jamone

Keyword(s):

Emotion Expression ◽

Human Robot Interaction ◽

Robot Interaction ◽

Human Emotion ◽

Important Concept ◽

Proposed Model ◽

Arousal Model ◽

Viable Model

Affordances are an important concept in cognition, which can be applied to robots in order to perform a successful human-robot interaction (HRI). In this paper we explore and discuss the idea of emotional affordances and propose a viable model for implementation into HRI. We consider “2-ways” affordances: perceived object triggering an emotion, and perceived human emotion expression triggering an action. In order to make the implementation generic, the proposed model includes a library that can be customised depending on the specific robot and application’s scenario. We present the AAA (Affordance-Appraisal-Arousal) model, which incorporates Plutchik’s Wheel of Emotions, and show some examples of simulation and possible scenarios.

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A Power Assistant Algorithm Based on Human–Robot Interaction Analysis for Improving System Efficiency and Riding Experience of E-Bikes

Sustainability ◽

10.3390/su13020768 ◽

2021 ◽

Vol 13 (2) ◽

pp. 768

Author(s):

Deok Ha Kim ◽

Dongun Lee ◽

Yeongjin Kim ◽

Sungjun Kim ◽

Dongjun Shin

Keyword(s):

Energy Consumption ◽

Interaction Analysis ◽

Rear Wheel ◽

Human Robot Interaction ◽

Robot Interaction ◽

Daily Lives ◽

Electric Bicycle ◽

Leg Kinematics ◽

Efficient Power ◽

Power Assistance

As robots are becoming more accessible in our daily lives, the interest in physical human–robot interaction (HRI) is rapidly increasing. An electric bicycle (E-bike) is one of the best examples of HRI, because a rider simultaneously actuates the rear wheel of the E-bike in close proximity. Most commercially available E-bikes employ a control methodology known as a power assistant system (PAS). However, this type of system cannot offer fully efficient power assistance for E-bikes since it does not account for the biomechanics of riders. In order to address this issue, we propose a control algorithm to increase the efficiency and enhance the riding experience of E-bikes by implementing the control parameters acquired from analyses of human leg kinematics and muscular dynamics. To validate the proposed algorithm, we have evaluated and compared the performance of E-bikes in three different conditions: (1) without power assistance, (2) assistance with a PAS algorithm, and (3) assistance with the proposed algorithm. Our algorithm required 5.09% less human energy consumption than the PAS algorithm and 11.01% less energy consumption than a bicycle operated without power assistance. Our algorithm also increased velocity stability by 11.89% and acceleration stability by 27.28%, and decreased jerk by 12.36% in comparison to the PAS algorithm.

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Design-Centered HRI Governance for Healthcare Robots

Journal of Healthcare Engineering ◽

10.1155/2022/3935316 ◽

2022 ◽

Vol 2022 ◽

pp. 1-8

Author(s):

Yueh-Hsuan Weng ◽

Yasuhisa Hirata

Keyword(s):

Decision Making ◽

Human Robot Interaction ◽

Robotic Systems ◽

Privacy Risk ◽

Robot Interaction ◽

Daily Lives ◽

Ethical Concerns ◽

Recent Developments ◽

And Robotics

Recent developments have shown that not only are AI and robotics growing more sophisticated, but also these fields are evolving together. The applications that emerge from this trend will break current limitations and ensure that robotic decision making and functionality are more autonomous, connected, and interactive in a way which will support people in their daily lives. However, in areas such as healthcare robotics, legal and ethical concerns will arise as increasingly advanced intelligence functions are incorporated into robotic systems. Using a case study, this paper proposes a unique design-centered approach which tackles the issue of data protection and privacy risk in human-robot interaction.

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System and method for recognizing human emotion state based on analysis of speech and facial feature extraction; applications to human-robot interaction

2016 4th International Conference on Robotics and Mechatronics (ICROM) ◽

10.1109/icrom.2016.7886857 ◽

2016 ◽

Cited By ~ 1

Author(s):

Mohammad Rabiei ◽

Alessandro Gasparetto

Keyword(s):

Feature Extraction ◽

Facial Feature ◽

Human Robot Interaction ◽

Robot Interaction ◽

Human Emotion ◽

Facial Feature Extraction

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Allocentric Emotional Affordances in HRI: The Multimodal Binding

Multimodal Technologies and Interaction ◽

10.3390/mti2040078 ◽

2018 ◽

Vol 2 (4) ◽

pp. 78 ◽

Cited By ~ 2

Author(s):

Jordi Vallverdú ◽

Gabriele Trovato ◽

Lorenzo Jamone

Keyword(s):

Human Robot Interaction ◽

Human Cognition ◽

Robot Interaction ◽

Numerical Examples ◽

Human Emotion ◽

Proposed Model ◽

Arousal Model ◽

Multimodal Perception ◽

Viable Model

The concept of affordance perception is one of the distinctive traits of human cognition; and its application to robots can dramatically improve the quality of human-robot interaction (HRI). In this paper we explore and discuss the idea of “emotional affordances” by proposing a viable model for implementation into HRI; which considers allocentric and multimodal perception. We consider “2-ways” affordances: perceived object triggering an emotion; and perceived human emotion expression triggering an action. In order to make the implementation generic; the proposed model includes a library that can be customised depending on the specific robot and application scenario. We present the AAA (Affordance-Appraisal-Arousal) model; which incorporates Plutchik’s Wheel of Emotions; and we outline some numerical examples of how it can be used in different scenarios.

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