scholarly journals Real-life emotion detection from speech in human-robot interaction: experiments across diverse corpora with child and adult voices

2011 ◽  
Author(s):  
Marie Tahon ◽  
Agnes Delaborde ◽  
Laurence Devillers
Keyword(s):  
Real Life ◽  
Human Robot Interaction ◽  
Emotion Detection ◽  
Robot Interaction

scholarly journals Should my robot know what's best for me? Human–robot interaction between user experience and ethical design

AI & Society ◽  
2021 ◽  
Author(s):  
Nora Fronemann ◽  
Kathrin Pollmann ◽  
Wulf Loh
Keyword(s):  
User Experience ◽  
Interaction Design ◽  
Real Life ◽  
Well Being ◽  
Design Principles ◽  
Human Robot Interaction ◽  
Ethical Challenges ◽  
Original Design ◽  
Robot Interaction ◽  
Ethical Design

AbstractTo integrate social robots in real-life contexts, it is crucial that they are accepted by the users. Acceptance is not only related to the functionality of the robot but also strongly depends on how the user experiences the interaction. Established design principles from usability and user experience research can be applied to the realm of human–robot interaction, to design robot behavior for the comfort and well-being of the user. Focusing the design on these aspects alone, however, comes with certain ethical challenges, especially regarding the user’s privacy and autonomy. Based on an example scenario of human–robot interaction in elder care, this paper discusses how established design principles can be used in social robotic design. It then juxtaposes these with ethical considerations such as privacy and user autonomy. Combining user experience and ethical perspectives, we propose adjustments to the original design principles and canvass our own design recommendations for a positive and ethically acceptable social human–robot interaction design. In doing so, we show that positive user experience and ethical design may be sometimes at odds, but can be reconciled in many cases, if designers are willing to adjust and amend time-tested design principles.

scholarly journals The Importance of Realism, Character, and Genre: How Theatre Can Support the Creation of Likeable Sociable Robots

2020 ◽  
Author(s):  
Louise LePage
Keyword(s):  
Real Life ◽  
Humanoid Robots ◽  
Human Robot Interaction ◽  
Romantic Comedy ◽  
Robot Interaction ◽  
Narrative Studies ◽  
Effective Performance ◽  
The Creation ◽  
Carry Over ◽  
And Robotics

AbstractStage plays, theories of theatre, narrative studies, and robotics research can serve to identify, explore, and interrogate theatrical elements that support the effective performance of sociable humanoid robots. Theatre, including its parts of performance, aesthetics, character, and genre, can also reveal features of human–robot interaction key to creating humanoid robots that are likeable rather than uncanny. In particular, this can be achieved by relating Mori's (1970/2012) concept of total appearance to realism. Realism is broader and more subtle in its workings than is generally recognised in its operationalization in studies that focus solely on appearance. For example, it is complicated by genre. A realistic character cast in a detective drama will convey different qualities and expectations than the same character in a dystopian drama or romantic comedy. The implications of realism and genre carry over into real life. As stage performances and robotics studies reveal, likeability depends on creating aesthetically coherent representations of character, where all the parts coalesce to produce a socially identifiable figure demonstrating predictable behaviour.

scholarly journals Gentle Versus Strong Touch Classification: Preliminary Results, Challenges, and Potentials

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3033
Author(s):  
Soheil Keshmiri ◽  
Masahiro Shiomi ◽  
Hidenobu Sumioka ◽  
Takashi Minato ◽  
Hiroshi Ishiguro
Keyword(s):  
Preliminary Investigation ◽  
Real Life ◽  
Human Robot Interaction ◽  
Machine Learning Algorithms ◽  
Robot Interaction ◽  
Affective Communication ◽  
Assistive Robots ◽  
Socially Assistive Robots ◽  
Average Accuracy ◽  
Different Types

Touch plays a crucial role in humans’ nonverbal social and affective communication. It then comes as no surprise to observe a considerable effort that has been placed on devising methodologies for automated touch classification. For instance, such an ability allows for the use of smart touch sensors in such real-life application domains as socially-assistive robots and embodied telecommunication. In fact, touch classification literature represents an undeniably progressive result. However, these results are limited in two important ways. First, they are mostly based on overall (i.e., average) accuracy of different classifiers. As a result, they fall short in providing an insight on performance of these approaches as per different types of touch. Second, they do not consider the same type of touch with different level of strength (e.g., gentle versus strong touch). This is certainly an important factor that deserves investigating since the intensity of a touch can utterly transform its meaning (e.g., from an affectionate gesture to a sign of punishment). The current study provides a preliminary investigation of these shortcomings by considering the accuracy of a number of classifiers for both, within- (i.e., same type of touch with differing strengths) and between-touch (i.e., different types of touch) classifications. Our results help verify the strength and shortcoming of different machine learning algorithms for touch classification. They also highlight some of the challenges whose solution concepts can pave the path for integration of touch sensors in such application domains as human–robot interaction (HRI).

scholarly journals A Multimodal Emotion Detection System during Human–Robot Interaction

Sensors ◽  
2013 ◽  
Vol 13 (11) ◽  
pp. 15549-15581 ◽  
Author(s):  
Fernando Alonso-Martín ◽  
María Malfaz ◽  
João Sequeira ◽  
Javier Gorostiza ◽  
Miguel Salichs
Keyword(s):  
Detection System ◽  
Human Robot Interaction ◽  
Emotion Detection ◽  
Robot Interaction

scholarly journals Hybrid Pneumatic-Hydraulic Actuator with Adaptable Stiffness

2020 ◽  
Vol 8 (6) ◽  
pp. 179-183
Keyword(s):  
Real Life ◽  
Human Robot Interaction ◽  
Muscle Performance ◽  
Hydraulic Actuator ◽  
Robot Interaction ◽  
Main Challenge ◽  
Different Types ◽  
Mckibben Muscle ◽  
Parallel Configuration ◽  
Hybrid Actuator

This work presents a method to control the stiffness of a hybrid actuator. The resulting stiffness is required to meet the conditions of real life applications, such as human prosthetics, human-robot interaction, and delicate robot interaction. The hybrid actuator is basically a pneumatic-hydraulic muscle, which can operate simultaneously in both pneumatic and hydraulic modes. The main challenge in this work is to manage the switching between pneumatic and hydraulic modes. In pneumatic mode when a load is applied to the actuator, air in the tank is allowed to compress resulting in muscle extension. While in hydraulic mode, the fluid is pressurized and the resultant system stiffness is higher. In both cases, the McKibben muscle is full with hydraulic fluid. It has been shown that the performance of the actuator is mostly the same in terms of response and bandwidth in both modes of operation. The use of different types of controllers to improve the system performance is investigated. It is found that the parallel configuration combined with PID controller is the best solution for achieving the required muscle performance.

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