Companion Robots Research Articles

Learning a foreign language vocabulary with a companion robot

Modern emotional companion robots can support multimodal communicative interaction with humans using speech, gestures, and facial expressions. This paper researches the potential of a social robot in the educational process: in a situation of learning a foreign language vocabulary. We have compared a classic text interface for word-learning with a companion robot, orally supporting the learning process of students (43 people, 34 women, average age 22.5years). It was shown that selection of one of the two methods does not affect the efficiency of word memorization, however, most of the students appreciate the robot as an assistant and indicate is as a preferable, or one of the possible learning tools in their future studies. The obtained results open up further prospects for using emotional companion robots in the educational process.

The social robot companion to support homecare nurses: The guardian study protocol

IntroductionThe reduction of the older people's self-sufficiency and the increase in the need for help in daily activities has a significant impact on the person and their caregivers. The primary objective of the GUARDIAN project is to enable the older people to live as long as possible at home, by means of the GUARDIAN socio-technical platform. Methodsand Analysis: The GUARDIAN platform consists of two connected apps: one dedicated to the caregiver (Caregiver App) and one dedicated to the older people (Senior App), plus a robot (Misty II), to provide coaching in an engaging modality. The study is designed as a technical feasibility pilot to test the GUARDIAN system on a group of older people. DiscussionsThe proposed solution reflects the real wants and needs of the older people person, increasing the acceptability of the system. In addition, the GUARDIAN project has the potential to have distinguished two phases of testing, so that changes can be made to the platform between the first and second phases, using data, both qualitative and quantitative, collected after the first phase. Ethics and disseminationThe study was approved by the Ethic Committee of the IRCCS INRCA. It was recorded in ClinicalTrials.gov on the number NCT05284292.

Communication-Focused Top-Down Design of Robotic Systems Based on Binary Decomposition

This article proposes a formal method of designing robotic systems focusing on communication between components, as well as standardization of the messages between those components. The objective is to design a robotic system controller in a systematic way, focusing on communication at an abstract agent level. Communication, thus organized, and its properly defined specification facilitate the system’s further development. The method uses a standard message structure, based on IEEE FIPA standards, for communication within robotic systems composed of agents. Communication-focused top-down design of robotic systems based on binary decomposition is proposed, and used to design a companion robot working in the kitchen environment. The implemented robotic system is verified based on whether or not the specification conforms to the specified requirements. The characteristics of the designed communication are evaluated. The obtained results prove that the proposed method of designing robotic systems is formally correct, it facilitates the implementation of agents, and separates specification of the system from its implementation. The method of designing robotic systems is correct and useful. The proposed formal notation facilitates understanding of how the system operates and organizes the design process. It puts the communication between system components at the forefront. The resulting system specification facilitates the implementation. The tools for experimental evaluation of its characteristics enable the confirmation that it fulfills the requirements, and that the communication between the system components is correct.

Companion robot can be a health keeper for the elderly: The effects of daily use of companion robot on medication compliance

Companion robot can be a health keeper for the elderly: The effects of daily use of companion robot on medication compliance

Emotion analysis using the interaction with companion robot in the depressed elderly in the community

Emotion analysis using the interaction with companion robot in the depressed elderly in the community

Effects of companion robots for socially isolated older adults

Effects of companion robots for socially isolated older adults

The effect of intervention using an emotional recognition coaching companion robot on the elderly people with depression

The effect of intervention using an emotional recognition coaching companion robot on the elderly people with depression

Usability Design of Human-Machine Interaction Interface of Child Companion Robot in Wireless Network

With the core and small-scale family structure, parents and children have less time and opportunities to interact, which leads to the lack of care and emotional companionship for preschool children, which is easy to cause physical and mental disorders. In response to this phenomenon, a series of child care robot products have emerged on the market and have continued to be the focus of attention in the past two years. However, such products are still generally deficient in terms of interaction and content. It is difficult for users to choose and use. This paper takes the design and application of remote parent-child interaction of preschool children’s escort machine as the research object. First, it examines the physical, psychological, and behavioral characteristics of escort robots, namely, preschool children. To sum up, the remote parent-child interaction design strategy of children’s escort robot products is proposed for the design practice and industry reference of this paper. The experimental results show that the children in the experimental group pay more attention to the main content and off-topic content than the control group, and the attention rate is more than 95%. To a certain extent, it can be said that the games in the system have the ability of parent-child interaction. This paper abandons the traditional research direction of pursuing human-computer interaction between childcare products and high technology. Instead, it studies parent-child emotional interaction, so that the emotional interaction between parents and children is not replaced by technology products but helps parents deepen the relationship with their children. Emotional interaction allows parents to truly accompany their children to grow up.

Non-pharmacological Intervention for Wandering Behavior in Dementia: A Systematic Review and Meta-analysis

Purpose: The present study aimed to explore the types of non-pharmacological interventions and evaluate their effectiveness in reducing wandering behavior in patientis with dementia.Methods: This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guideline. Searching eight databases (Cochrane, Ovid-MEDLINE, EMBASE, CINAHL, PubMed, PsycInfo, RISS, KISS, and KMBASE) yielded 899 related studies. Two reviewers independently assessed the quality of these studies, using Revised Cochrane risk of bias for randomized trials (ROB) 2.0 and Risk of Bias Assessment tool for Non-randomised Study (ROBANS) 2.0, based on this study design. The Algase Wandering Scale related to wandering behavior reported the standardized mean differences and their 95% confidence intervals.Results: A total of seven studies, consisting of four randomized controlled trials (RCTs) and three quasi-experimental studies, met the inclusion criteria. Among non-pharmacological interventions, aromatherapy was the most common. However, therapeutic contact, therapeutic companion robot, tailored activity program, combining physical activity, memory recall, music therapy, and multisensory stimulation were also performed in one study, respectively. In a meta-analysis (RevMan 5.4), non-pharmacological interventions reduced wandering behavior in patients with dementia and mild to moderate functional impairments (p=.003).Conclusion: The result of this meta-analysis suggests that non-pharmacological interventions are generally associated with reduced wandering behavior among patients with dementia and mild-moderate functional impairment. However, it is necessary to develop a more detailed non-pharmacological intervention for patients with dementia and wandering behavior according to their disease stage and characteristics.

Envisioning social drones in education.

Education is one of the major application fields in social Human-Robot Interaction. Several forms of social robots have been explored to engage and assist students in the classroom environment, from full-bodied humanoid robots to tabletop robot companions, but flying robots have been left unexplored in this context. In this paper, we present seven online remote workshops conducted with 20 participants to investigate the application area of Education in the Human-Drone Interaction domain; particularly focusing on what roles a social drone could fulfill in a classroom, how it would interact with students, teachers and its environment, what it could look like, and what would specifically differ from other types of social robots used in education. In the workshops we used online collaboration tools, supported by a sketch artist, to help envision a social drone in a classroom. The results revealed several design implications for the roles and capabilities of a social drone, in addition to promising research directions for the development and design in the novel area of drones in education.

Robot therapy pets get a starring role in Lightyear and in real life.

Roboticists are working on real-world versions of Sox, a robot companion in Lightyear, to play therapeutic roles.

Preliminary Study on Indonesian Word Recognition for Elder Companion Robot

Word recognition using deep learning is a simple approach to speech recognition in general. From this word-level recognition, the emotional expression recognition model. The emotion recognition model can be used to describe the important level of action on future planned hardware implementation. This research was conducted using MFCC as the feature extraction method from the audio data and using the CNN-LSTM approach for the emotional expression classifier. The model itself will be implemented into a humanoid robot to become a companion robot for the elderly. The model itself has 67% accuracy for emotion recognition and 97% accuracy for word recognition. However, the model only attained 20% accuracy in real-life testing using the humanoid robot as the model tends to overfitting as a result of the lack of data used in model training.

Inferring Stressors from Conversation: Towards an Emotional Support Robot Companion

Inferring Stressors from Conversation: Towards an Emotional Support Robot Companion

On the Navigation, Positioning and Wireless Communication of the Companion Robot in Outdoor Conditions

The dynamic process of demographic aging is an important reason for the systematic increase in the share of people with reduced mobility in Polish society [...]

SoHAM: A Sound-Based Human Activity Monitoring Framework for Home Service Robots

Monitoring daily activities is essential for home service robots to take care of the older adults who live alone in their homes. In this article, we proposed a sound-based human activity monitoring (SoHAM) framework by recognizing sound events in a home environment. First, the method of context-aware sound event recognition (CoSER) is developed, which uses contextual information to disambiguate sound events. The locational context of sound events is estimated by fusing the data from the distributed passive infrared (PIR) sensors deployed in the home. A two-level dynamic Bayesian network (DBN) is used to model the intratemporal and intertemporal constraints between the context and the sound events. Second, dynamic sliding time window-based human action recognition (DTW-HaR) is developed to estimate active sound event segments with their labels and durations, then infer actions and their durations. Finally, a conditional random field (CRF) model is proposed to predict human activities based on the recognized action, location, and time. We conducted experiments in our robot-integrated smart home (RiSH) testbed to evaluate the proposed framework. The obtained results show the effectiveness and accuracy of CoSER, action recognition, and human activity monitoring. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article is motivated by the goal to develop companion robots that can assist older adults living alone. Among many capabilities, monitoring human daily activities is an essential one for such robots. Though computer vision or wearable sensors-based methods have been developed by other researchers, they are not practical due to the privacy concern and intrusiveness. Sound-based daily activity recognition can address these concerns and offer a viable solution. In this regard, our proposed method adopts microphones on the robot and a small set of motion sensors distributed in the home. The proposed theoretical framework was tested in a small-scale mock-up apartment with promising results. Before such companion robots can be deployed to real homes for elderly care, there is a need to improve the robustness of the algorithms. More thorough tests in various realistic home environments should be conducted to fully evaluate the performance of the robots. In addition, privacy concern related to audio capture should be further mitigated.

Экономическая оценка количественных и качественных показателей новейшей инновационной разработки (на примере сервисного робота РОБИН)

The article proposes a new approach to the economic evaluation of office robotic devices on the example of the ROBIN companion robot developed in the Republic of Armenia. It is proposed to employ ROBIN in patient care in the healthcare sector. It is known that when a child is in prolonged isolation, there are problems with creating such conditions around him that will allow him to avoid getting into stressful situations. A method for determining the reduction in stress levels in sick children after their communication with the robot is described. According to the results of a comparative analysis of the results of calculations carried out using the quantitative and qualitative indicators of five com-panion robots taken from the literature, it was found that the innovative development created by Armenian researchers in the person of the ROBIN robot not only reduces stress in children who have been hospitalized for treatment, but is also not inferior to foreign analogues in their functions, and in some parameters even surpasses them. Key words: companion robots; stress level; comparative significance; weighting coeffi-cient; utility coefficient; quality level

Designing a Social Robot Companion to Support Homecare: Usability Results.

Earlier studies show frail seniors often experience loneliness and depression. Moreover, frailty can lead problems with medication and nutrition patterns. The availability of family care and/or nursing care at home is limited. Digital companions, such as social robots, could complement homecare nurses, thereby improving the quality of care to frail seniors. The Guardian project has co- designed with end-users, a social robot providing social company and health support. To assess the digital and co-created solution, usability evaluations have been conducted with 43 participants distributed as fairly as possible between frail seniors, family carers and professional nurses; in three different European areas: The Netherlands, Italy and Switzerland. The goal of this study is to evaluate if the GUARDIAN solution is accepted by the target users and also gather data on how to improve the system for ensuring added-value in home care. The iterative method based on user-centered approach put the end-users at the centre of the usability evaluation. Through thematic analysis of the qualitative datasets, we conclude that a high number of users accept the solution and describe it as useful. End-user needs have been mainly addressed but some new improvements have been pointed out by the participants and some other needs have been uncovered.

Perception for Autonomous Systems: A Measurement Perspective on Localization and Positioning

Autonomous systems are nowadays having an undisputed pervasiveness in modern society. Autonomous driving cars as well as applications of service robots (e.g., cleaning robots, companion robots, intelligent healthcare solutions, tour guided systems) are becoming more and more popular, and a general acceptance is now developing around such systems. Nonetheless, one of the major hurdles in building such applications relies on the capability of autonomous systems to understand their surroundings and then plan proper actions. The most popular solutions, which are gaining more and more attention, rely on artificial intelligence and deep learning as a means to perceive the structured and complex natural environment. Nonetheless, classical concepts of metrology, such as standard uncertainty, accuracy and precision, are still necessary for a clear and effective understanding of modern autonomous systems applications. In this paper, some fundamental measurement concepts will be reviewed in light of the autonomous systems domain, with an emphasis on localization and positioning problems for mobile robots. In particular, we will discuss and present the main issues and concepts that build around the statistical approach to measurements and the main role of uncertainties.

Companion bot with voice and facial emotion detection with PID based computer vision

We live in a world where technology embraces us and makes our lives easier. With increasing technological advances we feel the need for smart robotic assistants/companions to reduce the manual efforts taken by humans in day-to-day tasks and providing the necessary knowledge. In this paper, we develop a smart self companion robot that runs using human voice commands using some standard way of speech and this voice is converted into standard text form which is, in turn, converted into instructions and is fed to the robot, which further performs the necessary actions. The companion is fully automated with the capability of movement based on object tracking and voice response based on facial expression. The three main modules of this work are facial detection, emotion detection, and voice recognition. The bot is a wireless vehicle that will move along the human, interact with them depending on his/their emotions.

TV-Watching Robot: Toward Enriching Media Experience and Activating Human Communication

Viewing television (TV) with family and friends makes the experience more enjoyable. Recently, as more people watch TV programs on their mobile devices via the internet, opportunities to watch TV in groups are decreasing. We propose a companion robot to enhance human communication during the TV-viewing experience. The robot extracts keywords from the video, audio, and subtitle data of the TV program being watched, generates utterances from the keywords, and asks people questions related to the TV program. Viewers can chat with the robot, triggered by its questions. To confirm the utility of the robot, we conducted an experiment in which users watched TV with the robot. Results indicate that over 70% of the participants responded that the robot “promoted active conversations among people” and “created a more relaxed atmosphere.” Thus, our study demonstrates that a TV-watching robot can create novel and rich media experiences and stimulate communication among people.