Formalizing and guaranteeing human-robot interaction

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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Maximizing the Benefits of Participatory Design for Human–Robot Interaction Research With Older Adults

Human Factors The Journal of the Human Factors and Ergonomics Society ◽

10.1177/00187208211037465 ◽

2021 ◽

pp. 001872082110374

Author(s):

Wendy A. Rogers ◽

Travis Kadylak ◽

Megan A. Bayles

Keyword(s):

Older Adults ◽

Participatory Design ◽

Aging In Place ◽

Human Robot Interaction ◽

Multiple Stakeholders ◽

Robot Interaction ◽

Improve Design ◽

Assistive Robots ◽

Interaction Research

Objective We reviewed human–robot interaction (HRI) participatory design (PD) research with older adults. The goal was to identify methods used, determine their value for design of robots with older adults, and provide guidance for best practices. Background Assistive robots may promote aging-in-place and quality of life for older adults. However, the robots must be designed to meet older adults’ specific needs and preferences. PD and other user-centered methods may be used to engage older adults in the robot development process to accommodate their needs and preferences and to assure usability of emergent assistive robots. Method This targeted review of HRI PD studies with older adults draws on a detailed review of 26 articles. Our assessment focused on the HRI methods and their utility for use with older adults who have a range of needs and capabilities. Results Our review highlighted the importance of using mixed methods and including multiple stakeholders throughout the design process. These approaches can encourage mutual learning (to improve design by developers and to increase acceptance by users). We identified key phases used in HRI PD workshops (e.g., initial interview phase, series of focus groups phase, and presentation phase). These approaches can provide inspiration for future efforts. Conclusion HRI PD strategies can support designers in developing assistive robots that meet older adults’ needs, capabilities, and preferences to promote acceptance. More HRI research is needed to understand potential implications for aging-in-place. PD methods provide a promising approach.

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Service humanoid robotics: a novel interactive system based on bionic-companionship framework

PeerJ Computer Science ◽

10.7717/peerj-cs.674 ◽

2021 ◽

Vol 7 ◽

pp. e674

Author(s):

Jiaji Yang ◽

Esyin Chew ◽

Pengcheng Liu

Keyword(s):

Humanoid Robot ◽

Human Robot Interaction ◽

Service Robot ◽

Interactive System ◽

The Novel ◽

Image Captioning ◽

Robot Interaction ◽

Interactive Environment ◽

Speech Interaction

At present, industrial robotics focuses more on motion control and vision, whereas humanoid service robotics (HSRs) are increasingly being investigated and researched in the field of speech interaction. The problem and quality of human-robot interaction (HRI) has become a widely debated topic in academia. Especially when HSRs are applied in the hospitality industry, some researchers believe that the current HRI model is not well adapted to the complex social environment. HSRs generally lack the ability to accurately recognize human intentions and understand social scenarios. This study proposes a novel interactive framework suitable for HSRs. The proposed framework is grounded on the novel integration of Trevarthen’s (2001) companionship theory and neural image captioning (NIC) generation algorithm. By integrating image-to-natural interactivity generation and communicating with the environment to better interact with the stakeholder, thereby changing from interaction to a bionic-companionship. Compared to previous research a novel interactive system is developed based on the bionic-companionship framework. The humanoid service robot was integrated with the system to conduct preliminary tests. The results show that the interactive system based on the bionic-companionship framework can help the service humanoid robot to effectively respond to changes in the interactive environment, for example give different responses to the same character in different scenes.

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A Real-Time Sensor Based Hand Gesture Controlled Robotic Wheelchair for Assisting People with Disabilities

GUB Journal of Science and Engineering ◽

10.3329/gubjse.v7i0.54016 ◽

2021 ◽

pp. 85-93

Author(s):

Muhammad Aminur Rahaman ◽

Md Jahidul Islam ◽

Sumaiya Kabir ◽

Ayesha Khatun

Keyword(s):

Physical Disabilities ◽

Human Robot Interaction ◽

Hand Movements ◽

Hand Gesture ◽

Robot Hand ◽

Science And Engineering ◽

Robot Interaction ◽

People With Physical Disabilities ◽

Robotic Wheelchair

Currently, thousands of people are suffering from paralysis. They have difficulties with speaking and walking. So we’ve developed a new kind of robot that can help those people who can’t walk or speak. By utilizing this robot (hand gloves or wheelchair handle) and gesture-based regulators, people with physical disabilities will improve their quality of life. The robot of the proposal has two components, one is the controller of the motion, and the other is the Robotic Wheelchair (RW). Where one can easily interact with the robotic-base wheelchair-using sensor-based hand gesture. With this human-robot interaction, a patient can quite easily control the robot and can move freely. In addition, the required patients may use gestures (hand gloves or wheelchair handle) to express their needs. Furthermore, we will reduce the effort to regulate the RW and hand movements with this device, that’s really difficult for disabled or dumb people. Our device can run with approximately 94% accuracy and very minimal delay. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 7, Dec 2020 P 85-93

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Would a robot trust you? Developmental robotics model of trust and theory of mind

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2018.0032 ◽

2019 ◽

Vol 374 (1771) ◽

pp. 20180032 ◽

Cited By ~ 10

Author(s):

Samuele Vinanzi ◽

Massimiliano Patacchiola ◽

Antonio Chella ◽

Angelo Cangelosi

Keyword(s):

Theory Of Mind ◽

Cognitive Architecture ◽

Critical Issue ◽

Trust Model ◽

Human Robot Interaction ◽

Sources Of Information ◽

Developmental Robotics ◽

Robot Interaction ◽

Joint Task

Trust is a critical issue in human–robot interactions: as robotic systems gain complexity, it becomes crucial for them to be able to blend into our society by maximizing their acceptability and reliability. Various studies have examined how trust is attributed by people to robots, but fewer have investigated the opposite scenario, where a robot is the trustor and a human is the trustee. The ability for an agent to evaluate the trustworthiness of its sources of information is particularly useful in joint task situations where people and robots must collaborate to reach shared goals. We propose an artificial cognitive architecture based on the developmental robotics paradigm that can estimate the trustworthiness of its human interactors for the purpose of decision making. This is accomplished using Theory of Mind (ToM), the psychological ability to assign to others beliefs and intentions that can differ from one’s owns. Our work is focused on a humanoid robot cognitive architecture that integrates a probabilistic ToM and trust model supported by an episodic memory system. We tested our architecture on an established developmental psychological experiment, achieving the same results obtained by children, thus demonstrating a new method to enhance the quality of human and robot collaborations. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.

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Natural language guided object retrieval in images

Acta Informatica ◽

10.1007/s00236-021-00400-2 ◽

2021 ◽

Vol 58 (4) ◽

pp. 243-261

Author(s):

Ahmad Ostovar ◽

Suna Bensch ◽

Thomas Hellström

Keyword(s):

Natural Language ◽

Spatial Relations ◽

Human Robot Interaction ◽

Surveillance Systems ◽

Neural Net ◽

Robot Interaction ◽

Surrounding Environment ◽

Bounding Boxes ◽

Image Caption

AbstractThe ability to understand the surrounding environment and being able to communicate with interacting humans are important functionalities for many automated systems where visual input (e.g., images, video) and natural language input (speech or text) have to be related to each other. Possible applications are automatic image caption generation, interactive surveillance systems, or human robot interaction. In this paper, we propose algorithms for automatic responses to natural language queries about an image. Our approach uses a predefined neural net for detection of bounding boxes and objects in images, spatial relations between bounding boxes are modeled with a neural net, the queries are analyzed with a syntactic parser, and algorithms to map natural language to properties in the images are introduced. The algorithms make use of semantic similarity and antonyms. We evaluate the performance of our approach with test users assessing the quality of our system’s generated answers.

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Importance of Touch for Conveying Affection in a Multimodal Interaction with a Small Humanoid Robot

International Journal of Humanoid Robotics ◽

10.1142/s0219843615500024 ◽

2015 ◽

Vol 12 (01) ◽

pp. 1550002 ◽

Cited By ~ 12

Author(s):

Martin D. Cooney ◽

Shuichi Nishio ◽

Hiroshi Ishiguro

Keyword(s):

Social Intelligence ◽

Humanoid Robot ◽

Multimodal Interaction ◽

Human Robot Interaction ◽

Robot Interaction ◽

Main Challenge ◽

Short Video ◽

High Degree ◽

Companion Robots

To be accepted as a part of our everyday lives, companion robots will require the capability to communicate socially, recognizing people's behavior and responding appropriately. In particular, we hypothesized that a humanoid robot should be able to recognize affectionate touches conveying liking or dislike because (a) a humanoid form elicits expectations of a high degree of social intelligence, (b) touch behavior plays a fundamental and crucial role in human bonding, and (c) robotic responses providing affection could contribute to people's quality of life. The hypothesis that people will seek to affectionately touch a robot needed to be verified because robots are typically not soft or warm like humans, and people can communicate through various other modalities such as vision and sound. The main challenge faced was that people's social norms are highly complex, involving behavior in multiple channels. To deal with this challenge, we adopted an approach in which we analyzed free interactions and also asked participants to rate short video-clips depicting human–robot interaction. As a result, we verified that touch plays an important part in the communication of affection from a person to a humanoid robot considered capable of recognizing cues in touch, vision, and sound. Our results suggest that designers of affectionate interactions with a humanoid robot should not ignore the fundamental modality of touch.

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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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An Abstraction Layer Exploiting Voice Assistant Technologies for Effective Human—Robot Interaction

Applied Sciences ◽

10.3390/app11199165 ◽

2021 ◽

Vol 11 (19) ◽

pp. 9165

Author(s):

Ruben Alonso ◽

Emanuele Concas ◽

Diego Reforgiato Recupero

Keyword(s):

Ad Hoc ◽

Speech Disorders ◽

Human Robot Interaction ◽

Use Case ◽

Robot Interaction ◽

Fully Integrated ◽

Abstraction Layer ◽

The One ◽

Robotic Wheelchairs

A lot of people have neuromuscular problems that affect their lives leading them to lose an important degree of autonomy in their daily activities. When their disabilities do not involve speech disorders, robotic wheelchairs with voice assistant technologies may provide appropriate human–robot interaction for them. Given the wide improvement and diffusion of Google Assistant, Apple’s Siri, Microsoft’s Cortana, Amazon’s Alexa, etc., such voice assistant technologies can be fully integrated and exploited in robotic wheelchairs to improve the quality of life of affected people. As such, in this paper, we propose an abstraction layer capable of providing appropriate human–robot interaction. It allows use of voice assistant tools that may trigger different kinds of applications for the interaction between the robot and the user. Furthermore, we propose a use case as a possible instance of the considered abstraction layer. Within the use case, we chose existing tools for each component of the proposed abstraction layer. For example, Google Assistant was employed as a voice assistant tool; its functions and APIs were leveraged for some of the applications we deployed. On top of the use case thus defined, we created several applications that we detail and discuss. The benefit of the resulting Human–Computer Interaction is therefore two-fold: on the one hand, the user may interact with any of the developed applications; on the other hand, the user can also rely on voice assistant tools to receive answers in the open domain when the statement of the user does not enable any of the applications of the robot. An evaluation of the presented instance was carried out using the Software Architecture Analysis Method, whereas the user experience was evaluated through ad-hoc questionnaires. Our proposed abstraction layer is general and can be instantiated on any robotic platform including robotic wheelchairs.

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A MLP-Hedge-Algebras Admittance Controller for Physical Human–Robot Interaction

Applied Sciences ◽

10.3390/app11125459 ◽

2021 ◽

Vol 11 (12) ◽

pp. 5459

Author(s):

Nguyen-Van Toan ◽

Phan-Bui Khoi ◽

Soo-Yeong Yi

Keyword(s):

Neural Network ◽

Fuzzy Logic ◽

Multilayer Perceptron ◽

Human Robot Interaction ◽

Input Output ◽

Robot Interaction ◽

Inference Mechanism ◽

Safety Issues ◽

First Time

Recently, the identification of inertia and damping matrices (IIDM) and safety issues, as well as natural cooperation, are interestingly considered to enhance the quality of the physical human–robot interaction (pHRI). To cover all of these issues, advanced admittance controllers, such as those based on fuzzy logic or hedge algebras, have been formulated and successfully applied in several industrial problems. However, the inference mechanism of those kinds of controllers causes the discreteness of the super surface describing the input–output relationship in the Cartesian coordinates. As a consequence, the quality of the safe-natural cooperation between humans and robots is negatively affected. This paper presents an alternative admittance controller for pHRI by using a combination of hedge algebras and multilayer perceptron neural network (MLP), whose purpose is to create a more accurate inference mechanism for the admittance controller. To our best knowledge, this is the first time that such a neural network is considered for the inference mechanism of hedge algebras and also the first time that such an admittance controller is used for pHRI. The proposed admittance controller is verified on a teaching task using a 6-DOF manipulator. Experimental results have shown that the proposed method provides better cooperation compared with previous methods.

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