Effect of agent embodiment on the elder user enjoyment of a game

International audienceThis paper presents a study that compared the elder user enjoyment of a game of trivia in three conditions: participants playing the game with a laptop PC vs. a robot vs. a virtual agent. Statistical analysis did not show any significant difference of the three devices on user enjoyment while qualitative analysis revealed a preference for the laptop PC condition, followed by the robot and the virtual agent. The elderly participants were concentrated on the task performance rather on the interaction with systems. They preferred laptop PC condition mainly because there were less interfaces distracting them from performing the task proposed by the game. Further, the robot was preferred to a virtual agent because of its physical presence. Some issues of the experiment design are raised and directions for future research are suggested to gain more insight into the effects of agent embodiment on human-agent interaction

Socially assistive robotics for post-stroke rehabilitation

BACKGROUND: Although there is a great deal of success in rehabilitative robotics applied to patient recovery post stroke, most of the research to date has dealt with providing physical assistance. However, new rehabilitation studies support the theory that not all therapy need be hands-on. We describe a new area, called socially assistive robotics, that focuses on non-contact patient/user assistance. We demonstrate the approach with an implemented and tested post-stroke recovery robot and discuss its potential for effectiveness. RESULTS: We describe a pilot study involving an autonomous assistive mobile robot that aids stroke patient rehabilitation by providing monitoring, encouragement, and reminders. The robot navigates autonomously, monitors the patient's arm activity, and helps the patient remember to follow a rehabilitation program. We also show preliminary results from a follow-up study that focused on the role of robot physical embodiment in a rehabilitation context. CONCLUSION: We outline and discuss future experimental designs and factors toward the development of effective socially assistive post-stroke rehabilitation robots

Personality factors and acceptability of socially assistive robotics in teachers with and without specialized training for children with disability

Personality factors can be predictors of acceptability and intention to use new technologies, especially regarding education and care fields in the whole lifespan. The aim of this study was to evaluate the predictive factors and attitudes of curricular and specialized teachers towards socially assistive robotics and the intention to use robots in teaching activities. In our research, we investigated the impact of the personality factors measured with the Big Five Questionnaire, on acceptability questionnaires derived by Eurobarometer and by the model Unified Theory of the Acceptance and Use of Technology (UTAUT), administered respectively before and after showing the possible uses of the robot NAO in education and teaching. The study was conducted in four schools, participants were 114 teachers (52.07 ± 8.22), aged 26 to 68 years, of the primary and middle school level. The results highlight the primary role of the personality factors Openness to Experience and Extraversion for promoting the acceptability and reduce the prejudicial reject regarding the use of educational and assistive robotic technologies. In conclusion, for using at best robotics in education, teachers need to receive appropriate training - also on the basis of their attitudes and personality traits - to learn how to plan their educational activities integrating the robotics tool

Assistive VR Gym: Interactions with Real People to Improve Virtual Assistive Robots

Versatile robotic caregivers could benefit millions of people worldwide, including older adults and people with disabilities. Recent work has explored how robotic caregivers can learn to interact with people through physics simulations, yet transferring what has been learned to real robots remains challenging. Virtual reality (VR) has the potential to help bridge the gap between simulations and the real world. We present Assistive VR Gym (AVR Gym), which enables real people to interact with virtual assistive robots. We also provide evidence that AVR Gym can help researchers improve the performance of simulation-trained assistive robots with real people. Prior to AVR Gym, we trained robot control policies (Original Policies) solely in simulation for four robotic caregiving tasks (robot-assisted feeding, drinking, itch scratching, and bed bathing) with two simulated robots (PR2 from Willow Garage and Jaco from Kinova). With AVR Gym, we developed Revised Policies based on insights gained from testing the Original policies with real people. Through a formal study with eight participants in AVR Gym, we found that the Original policies performed poorly, the Revised policies performed significantly better, and that improvements to the biomechanical models used to train the Revised policies resulted in simulated people that better match real participants. Notably, participants significantly disagreed that the Original policies were successful at assistance, but significantly agreed that the Revised policies were successful at assistance. Overall, our results suggest that VR can be used to improve the performance of simulation-trained control policies with real people without putting people at risk, thereby serving as a valuable stepping stone to real robotic assistance.Comment: IEEE International Conference on Robot and Human Interactive Communication (RO-MAN 2020), 8 pages, 8 figures, 2 table

A framework for anomaly detection in activities of daily living using an assistive robot

This paper presents an overview of an ongoing research to incorporate an assistive robotic platform towards improved detection of anomalies in daily living activities of older adults. This involves learning human daily behavioural routine and detecting deviation from the known routine which can constitute an abnormality. Current approaches suffer from high rate of false alarms, therefore, lead to dissatisfaction by clients and carers. This may be connected to behavioural changes of human activities due to seasonal or other physical factors. To address this, a framework for anomaly detection is proposed which incorporates an assistive robotic platform as an intermediary. Instances classified as anomalous will first be confirmed from the monitored individual through the intermediary. The proposed framework has the potential of mitigating the false alarm rate generated by current approaches

An open platform for the design of social robot embodiments for face- to-face communication

The role of the physical embodiment of a social robot is of key importance during the interaction with humans. If we want to study the interactions we need to be able to change the robot’s embodiment to the nature of the experiment. Nowadays, researchers build one-off robots from scratch or choose to use a commercially available platform. This is justified by the time and budget constraints and the lack of design tools for social robots. In this work, we introduce an affordable open source platform to accelerate the design and production of novel social robot embodiments, with a focus on face-to-face communication. We describe an experiment where Industrial Design students created physical embodiments for 10 new social robots using our platform, detailing the design methodology followed during the different steps of the process. The paper gives an overview of the platform modules used by each of the robots, the skinning techniques employed, as well as the perceived usability of the platform. In summary, we show that our platform (1) enables non-experts to design new social robot embodiments, (2) allows a wide variety of different robots to be built with the same building blocks, and (3) affords itself to being adapted and extended

A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics

In this work, we present an unobtrusive and non-invasive perception framework based on the synergy between two main acquisition systems: the Touch-Me Pad, consisting of two electronic patches for physiological signal extraction and processing; and the Scene Analyzer, a visual-auditory perception system specifically designed for the detection of social and emotional cues. It will be explained how the information extracted by this specific kind of framework is particularly suitable for social robotics applications and how the system has been conceived in order to be used in human-robot interaction scenarios