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27 pages, 3523 KiB

Open AccessArticle

Design of a Huggable Social Robot with Affective Expressions Using Projected Images

by Eleuda Nunez, Masakazu Hirokawa and Kenji Suzuki

Appl. Sci. 2018, 8(11), 2298; https://0-doi-org.brum.beds.ac.uk/10.3390/app8112298 - 19 Nov 2018

Cited by 10 | Viewed by 3936

We introduce Pepita, a caricatured huggable robot capable of sensing and conveying affective expressions by means of tangible gesture recognition and projected avatars. This study covers the design criteria, implementation and performance evaluation of the different characteristics of the form and function of [...] Read more.

We introduce Pepita, a caricatured huggable robot capable of sensing and conveying affective expressions by means of tangible gesture recognition and projected avatars. This study covers the design criteria, implementation and performance evaluation of the different characteristics of the form and function of this robot. The evaluation involves: (1) the exploratory study of the different features of the device, (2) design and performance evaluation of sensors for affective interaction employing touch, and (3) design and implementation of affective feedback using projected avatars. Results showed that the hug detection worked well for the intended application and the affective expressions made with projected avatars were appropriated for this robot. The questionnaires analyzing users’ perception provide us with insights to guide the future designs of similar interfaces. Full article

(This article belongs to the Special Issue Social Robotics)

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18 pages, 3694 KiB

Open AccessArticle

Learning and Planning Based on Merged Experience from Multiple Situations for a Service Robot

by Zhixian Chen, Baoliang Zhao, Shijia Zhao, Ying Hu and Jianwei Zhang

Appl. Sci. 2018, 8(10), 1832; https://0-doi-org.brum.beds.ac.uk/10.3390/app8101832 - 06 Oct 2018

Cited by 2 | Viewed by 2184

Abstract

For a service robot, learning appropriate behaviours to acquire task knowledge and deliberation in various situations is essential, but the existing methods do not support merging the plan-based activity experiences from multiple situations in the same task. In this paper, an abstract method [...] Read more.

For a service robot, learning appropriate behaviours to acquire task knowledge and deliberation in various situations is essential, but the existing methods do not support merging the plan-based activity experiences from multiple situations in the same task. In this paper, an abstract method is introduced to integrate the empirical activity schemas of multiple situations, and a novel algorithm is presented to learn activity schema with abstract methods. Furthermore, a novel planner called the schema-based optimized planner (SBOP) is developed based on the learned activity schema, in which actions merging optimization and partially backtracking techniques are adopted. A simulation with a PR2 robot and a physical experiment is conducted to validate the proposed method. The results show that the robot can generate a plan to recover from failure automatically using the novel learning and planning method, given that the experienced exception has been merged in the activity schema. Owing to the improved autonomy, the proposed SBOP exhibits increased efficiency in dealing with tasks containing loops and multiple activity schema instances. This research presents a novel solution of how to merge activity experiences from multiple situations and generate an intelligent and efficient plan that could adapt to a dynamically changing environment. Full article

(This article belongs to the Special Issue Social Robotics)

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10 pages, 261 KiB

Open AccessArticle

Healthcare Students’ Ethical Considerations of Care Robots in The Netherlands

by Margo A. M. Van Kemenade, Johan F. Hoorn and Elly A. Konijn

Appl. Sci. 2018, 8(10), 1712; https://0-doi-org.brum.beds.ac.uk/10.3390/app8101712 - 20 Sep 2018

Cited by 6 | Viewed by 4242

Abstract

Background: Older adults are a rapidly growing group world-wide, requiring an increasing amount of healthcare. Technological innovations such as care robots may support the growing demand for care. However, hardly any studies address those who will most closely collaborate with care robots: the [...] Read more.

Background: Older adults are a rapidly growing group world-wide, requiring an increasing amount of healthcare. Technological innovations such as care robots may support the growing demand for care. However, hardly any studies address those who will most closely collaborate with care robots: the (trainee) healthcare professional. Methods: This study examined the moral considerations, perceptions of utility, and acceptance among trainee healthcare professionals toward different types of care robots in an experimental questionnaire design (N = 357). We also examined possible differences between participants’ intermediate and higher educational levels. Results: The results show that potential maleficence of care robots dominated the discussion in both educational groups. Assisting robots were seen as potentially the most maleficent. Both groups deemed companion robots least maleficent and most acceptable, while monitoring robots were perceived as least useful. Results further show that the acceptance of robots in care was more strongly associated with the participants’ moral considerations than with utility. Conclusions: Professional care education should include moral considerations and utility of robotics as emerging care technology. The healthcare and nursing students of today will collaborate with the robotic colleagues of tomorrow. Full article

(This article belongs to the Special Issue Social Robotics)

30 pages, 4951 KiB

Open AccessArticle

A Multi-Modal Person Recognition System for Social Robots

by Mohammad K. Al-Qaderi and Ahmad B. Rad

Appl. Sci. 2018, 8(3), 387; https://0-doi-org.brum.beds.ac.uk/10.3390/app8030387 - 06 Mar 2018

Cited by 16 | Viewed by 5966

Abstract

The paper presents a solution to the problem of person recognition by social robots via a novel brain-inspired multi-modal perceptual system. The system employs spiking neural network to integrate face, body features, and voice data to recognize a person in various social human-robot [...] Read more.

The paper presents a solution to the problem of person recognition by social robots via a novel brain-inspired multi-modal perceptual system. The system employs spiking neural network to integrate face, body features, and voice data to recognize a person in various social human-robot interaction scenarios. We suggest that, by and large, most reported multi-biometric person recognition algorithms require active participation by the subject and as such are not appropriate for social human-robot interactions. However, the proposed algorithm relaxes this constraint. As there are no public datasets for multimodal systems, we designed a hybrid dataset by integration of the ubiquitous FERET, RGB-D, and TIDIGITS datasets for face recognition, person recognition, and speaker recognition, respectively. The combined dataset facilitates association of facial features, body shape, and speech signature for multimodal person recognition in social settings. This multimodal dataset is employed for testing the algorithm. We assess the performance of the algorithm and discuss its merits against related methods. Within the context of the social robotics, the results suggest the superiority of the proposed method over other reported person recognition algorithms. Full article

(This article belongs to the Special Issue Social Robotics)

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18 pages, 8077 KiB

Open AccessArticle

Designing the Mind of a Social Robot

by Nicole Lazzeri, Daniele Mazzei, Lorenzo Cominelli, Antonio Cisternino and Danilo Emilio De Rossi

Appl. Sci. 2018, 8(2), 302; https://0-doi-org.brum.beds.ac.uk/10.3390/app8020302 - 19 Feb 2018

Cited by 30 | Viewed by 7790

Abstract

Humans have an innate tendency to anthropomorphize surrounding entities and have always been fascinated by the creation of machines endowed with human-inspired capabilities and traits. In the last few decades, this has become a reality with enormous advances in hardware performance, computer graphics, [...] Read more.

Humans have an innate tendency to anthropomorphize surrounding entities and have always been fascinated by the creation of machines endowed with human-inspired capabilities and traits. In the last few decades, this has become a reality with enormous advances in hardware performance, computer graphics, robotics technology, and artificial intelligence. New interdisciplinary research fields have brought forth cognitive robotics aimed at building a new generation of control systems and providing robots with social, empathetic and affective capabilities. This paper presents the design, implementation, and test of a human-inspired cognitive architecture for social robots. State-of-the-art design approaches and methods are thoroughly analyzed and discussed, cases where the developed system has been successfully used are reported. The tests demonstrated the system’s ability to endow a social humanoid robot with human social behaviors and with in-silico robotic emotions. Full article

(This article belongs to the Special Issue Social Robotics)

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18 pages, 3688 KiB

Open AccessArticle

Robotic Motion Learning Framework to Promote Social Engagement

by Rachael Burns, Myounghoon Jeon and Chung Hyuk Park

Appl. Sci. 2018, 8(2), 241; https://0-doi-org.brum.beds.ac.uk/10.3390/app8020241 - 05 Feb 2018

Cited by 7 | Viewed by 7127

Abstract

Imitation is a powerful component of communication between people, and it poses an important implication in improving the quality of interaction in the field of human–robot interaction (HRI). This paper discusses a novel framework designed to improve human–robot interaction through robotic imitation of [...] Read more.

Imitation is a powerful component of communication between people, and it poses an important implication in improving the quality of interaction in the field of human–robot interaction (HRI). This paper discusses a novel framework designed to improve human–robot interaction through robotic imitation of a participant’s gestures. In our experiment, a humanoid robotic agent socializes with and plays games with a participant. For the experimental group, the robot additionally imitates one of the participant’s novel gestures during a play session. We hypothesize that the robot’s use of imitation will increase the participant’s openness towards engaging with the robot. Experimental results from a user study of 12 subjects show that post-imitation, experimental subjects displayed a more positive emotional state, had higher instances of mood contagion towards the robot, and interpreted the robot to have a higher level of autonomy than their control group counterparts did. These results point to an increased participant interest in engagement fueled by personalized imitation during interaction. Full article

(This article belongs to the Special Issue Social Robotics)

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3443 KiB

Open AccessArticle

Enhancing Interpretation of Ambiguous Voice Instructions based on the Environment and the User’s Intention for Improved Human-Friendly Robot Navigation

by M. A. Viraj J. Muthugala, P. H. D. Arjuna S. Srimal and A. G. Buddhika P. Jayasekara

Appl. Sci. 2017, 7(8), 821; https://0-doi-org.brum.beds.ac.uk/10.3390/app7080821 - 10 Aug 2017

Cited by 10 | Viewed by 4082

Abstract

Human-friendly interactive features are preferred for domestic service robots. Humans prefer to use verbal communication in order to convey instructions to peers. Those voice instructions often include uncertain terms such as “little” and “far”. Therefore, the ability to quantify such information is mandatory [...] Read more.

Human-friendly interactive features are preferred for domestic service robots. Humans prefer to use verbal communication in order to convey instructions to peers. Those voice instructions often include uncertain terms such as “little” and “far”. Therefore, the ability to quantify such information is mandatory for human-friendly service robots. The meaning of such voice instructions depends on the environment and the intention of the user. Therefore, this paper proposes a method in order to interpret the ambiguities in user instructions based on the environment and the intention of the user. The actual intention of the user is identified by analyzing the pointing gestures accompanied with the voice instructions since pointing gestures can be used in order to express the intention of the user. A module called the motion intention switcher (MIS) has been introduced in order to switch the intention of the robot based on the arrangement of the environment and the point referred by the gesture. Experiments have been carried out in an artificially-created domestic environment. According to the experimental results, the behavior of the MIS is effective in identifying the actual intention of the user and switching the intention of the robot. Moreover, the proposed concept is capable of enhancing the uncertain information evaluation ability of robots. Full article

(This article belongs to the Special Issue Social Robotics)

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Review

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6041 KiB

Open AccessReview

Bibliometric Analysis of Social Robotics Research: Identifying Research Trends and Knowledgebase

by Cristian Mejia and Yuya Kajikawa

Appl. Sci. 2017, 7(12), 1316; https://0-doi-org.brum.beds.ac.uk/10.3390/app7121316 - 18 Dec 2017

Cited by 35 | Viewed by 5661

Abstract

As robotics becomes ubiquitous, there is increasing interest in understanding how to develop robots that better respond to social needs, as well as how robotics impacts society. This is evidenced by the growing rate of publications on social robotics. In this article, we [...] Read more.

As robotics becomes ubiquitous, there is increasing interest in understanding how to develop robots that better respond to social needs, as well as how robotics impacts society. This is evidenced by the growing rate of publications on social robotics. In this article, we analyze the citation network of academic articles on social robotics to understand its structure, reveal research trends and expose its knowledgebase. We found eight major clusters, namely robots as social partners, human factors and ergonomics on human robot interaction, robotics for children’s development, swarm robotics, emotion detection, assessment of robotic surgery, robots for the elderly and telepresence and human robot interaction in rescue robots. In addition, despite its social focus, social science literature as a source of knowledge is barely present. Research trends point to studies on applications, rather than to specific technologies or morphologies, and in particular, towards robots as partners, for child development and assistance for the elderly. Full article

(This article belongs to the Special Issue Social Robotics)

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