scholarly journals Human-Robot Interaction and Neuroprosthetics: A review of new technologies.

2017 ◽  
Vol 6 (3) ◽  
pp. 24-33 ◽  
Author(s):  
Angelo Cangelosi ◽  
Sara Invitto
Author(s):  
Alina Tausch ◽  
Annette Kluge

AbstractNew technologies are ever evolving and have the power to change human work for the better or the worse depending on the implementation. For human–robot interaction (HRI), it is decisive how humans and robots will share tasks and who will be in charge for decisions on task allocation. The aim of this online experiment was to examine the influence of different decision agents on the perception of a task allocation process in HRI. We assume that inclusion of the worker in the allocation will create more perceived work resources and will lead to more satisfaction with the allocation and the work results than a decision made by another agent. To test these hypotheses, we used a fictional production scenario where tasks were allocated to the participant and a robot. The allocation decision was either made by the robot, by an organizational unit, or by the participants themselves. We then looked for differences between those conditions. Our sample consisted of 151 people. In multiple ANOVAs, we could show that satisfaction with the allocation process, the solution, and with the result of the work process was higher in the condition where participants themselves were given agency in the allocation process compared to the other two. Those participants also experienced more task identity and autonomy. This has implications for the design of allocation processes: The inclusion of workers in task allocation can play a crucial role in leveraging the acceptance of HRI and in designing humane work systems in Industry 4.0.


Kybernetes ◽  
2016 ◽  
Vol 45 (8) ◽  
pp. 1257-1272 ◽  
Author(s):  
Hooman Samani

Purpose The purpose of this paper is to propose a novel method for evaluation of human-robot affection. The model is inspired by the scientific methods of human-human love evaluation. This paper would benefit the researchers in the field of developing new technologies where emotional interaction is involved. Design/methodology/approach Among the two available options of Functional Magnetic Resonance Imaging (fMRI) and user study, the latter is adopted and the conventional method of Love Attitude Scale is transformed for human-robot interaction as Lovotics (love + robotics) Love Attitude Scale. A user study is conducted to evaluate the emotional effect of interaction with the robot. Findings The proposed method is employed in order to evaluate the performance of Lovotics robot. In total, 20 users experienced interaction with Lovotics robot and answered questionnaires which were designed based on the psychology of love, especially to measure love scales between the participants and the robot. Data from the user study are analyzed statistically to evaluate the overall performance of the designed robot. Research limitations/implications Various aspects including human to robot love styles, robot to human love styles, overall love values and gender study are investigated during the data analysis. The concept of human-robot affection is still in initial stage of development. Personal and social robots are increasing and much limitation from artificial intelligence, mechanical development and integration still exist. Practical implications This is a multidisciplinary research field utilizing fundamentals concepts from robotics, artificial intelligence, philosophy, psychology, biology, anthropology, neuroscience, social science, computer science and engineering. Social implications Considering the recent technical advancement in robotics which is brining robots closer to home, this paper aims to bridge the gap between human and robot affection measurement. The final goal is to introduce robots to the society which are useful and can be especially used to take care of those in need such as elderly. Originality/value This paper is one of the first kind to get inspired from scientific human love evaluation methods and apply that to human-robot application.


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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