Socially Constrained Management Of Power Resources For Social Mobile Robots

Autonomous robots acting as companions or assistants in real social environments should be able to sustain and operate over an extended period of time. Generally, autonomous mobile robots draw power from batteries to operate various sensors, actuators and perform tasks. Batteries have a limited power life and take a long time to recharge via a power source, which may impede human-robot interaction and task performance. Thus, it is important for social robots to manage their energy, this paper discusses an approach to manage power resources on mobile robot with regard to social aspects for creating life-like autonomous social robots

Studying table-top manipulation tasks: a robust framework for object tracking in collaboration

Table-top object manipulation is a well-established test bed on which to study both basic foundations of general human-robot interaction and more specific collaborative tasks. A prerequisite, both for studies and for actual collaborative or assistive tasks, is the robust perception of any objects involved. This paper presents a real-time capable and ROS-integrated approach, bringing together state-of-the-art detection and tracking algorithms, integrating perceptual cues from multiple cameras and solving detection, sensor fusion and tracking in one framework. The highly scalable framework was tested in a HRI use-case scenario with 25 objects being reliably tracked under significant temporary occlusions. The use-case demonstrates the suitability of the approach when working with multiple objects in small table-top environments and highlights the versatility and range of analysis available with this framework

Human Attention Assessment Using A Machine Learning Approach with GAN-based Data Augmentation Technique Trained Using a Custom Dataset

Human–robot interactions require the ability of the system to determine if the user is paying attention. However, to train such systems, massive amounts of data are required. In this study, we addressed the issue of data scarcity by constructing a large dataset (containing ~120,000 photographs) for the attention detection task. Then, by using this dataset, we established a powerful baseline system. In addition, we extended the proposed system by adding an auxiliary face detection module and introducing a unique GAN-based data augmentation technique. Experimental results revealed that the proposed system yields superior performance compared to baseline models and achieves an accuracy of 88% on the test set. Finally, we created a web application for testing the proposed model in real time

Towards long-term social child-robot interaction: using multi-activity switching to engage young users

Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of an effective child-robot interaction (cHRI) to ensure the child remains engaged in the relationship and that educational goals are met. Typically, current cHRI research experiments focus on a single type of interaction activity (e.g. a game). However, these can suffer from a lack of adaptation to the child, or from an increasingly repetitive nature of the activity and interaction. In this paper, we motivate and propose a practicable solution to this issue: an adaptive robot able to switch between multiple activities within single interactions. We describe a system that embodies this idea, and present a case study in which diabetic children collaboratively learn with the robot about various aspects of managing their condition. We demonstrate the ability of our system to induce a varied interaction and show the potential of this approach both as an educational tool and as a research method for long-term cHRI

A systematic review of study results reported for the evaluation of robotic rollators from the perspective of users

© 2017 Informa UK Limited, trading as Taylor & Francis Group. Purpose: To evaluate the effectiveness and perception of robotic rollators (RRs) from the perspective of users. Methods: Studies identified in a previous systematic review published on 2016 on the methodology of studies evaluating RRs by the user perspective were re-screened for eligibility based on the following inclusion criteria: evaluation of the human–robot interaction from the user perspective, use of standardized outcome measurements, and quantitative presentation of study results. Results: Seventeen studies were eligible for inclusion. Due to the clinical and methodological heterogeneity across studies, a narrative synthesis of study results was conducted. We found conflicting results concerning the effectiveness of the robotic functionalities of the RRs. Only a few studies reported superior user performance or reduced physical demands with the RRs compared to unassisted conditions or conventional assistive mobility devices; however, without providing statistical evidence. The user perception of the RRs was found to be generally positive. Conclusions: There is still no sufficient evidence on the effectiveness of RRs from the user perspective. More well-designed, high-quality studies with adequate study populations, larger sample sizes, appropriate assessment strategies with outcomes specifically tailored to the robotic functionalities, and statistical analyses of results are required to evaluate RRs at a higher level of evidence.Implications for Rehabilitation RRs cover intelligent functionalities that focus on gait assistance, obstacle avoidance, navigation assistance, sit-to-stand transfer, body weight support or fall prevention. The evaluation from the user perspective is essential to ensure that RRs effectively address users’ needs, requirements and preferences. The evidence on the effectiveness of RRs is severely hampered by the low methodological quality of most of the available studies. RRs seem generally to be perceived as positive by the users. There is very limited evidence on the effectiveness and benefits of RRs compared to conventional assistive mobility devices. Further research with high methodological quality needs to be conducted to reach more robust conclusions about the effectiveness of RRs

Robot education peers in a situated primary school study: personalisation promotes child learning

The benefit of social robots to support child learning in an educational context over an extended period of time is evaluated. Specifically, the effect of personalisation and adaptation of robot social behaviour is assessed. Two autonomous robots were embedded within two matched classrooms of a primary school for a continuous two week period without experimenter supervision to act as learning companions for the children for familiar and novel subjects. Results suggest that while children in both personalised and non-personalised conditions learned, there was increased child learning of a novel subject exhibited when interacting with a robot that personalised its behaviours, with indications that this benefit extended to other class-based performance. Additional evidence was obtained suggesting that there is increased acceptance of the personalised robot peer over a non-personalised version. These results provide the first evidence in support of peer-robot behavioural personalisation having a positive influence on learning when embedded in a learning environment for an extended period of time

Service Robots in Catering Applications: A Review and Future Challenges.

“Hello, I’m the TERMINATOR, and I’ll be your server today”. Diners might soon be feeling this greeting, with Optimus Prime in the kitchen and Wall-E then sending your order to C-3PO. In our daily lives, a version of that future is already showing up. Robotics companies are designing robots to handle tasks, including serving, interacting, collaborating, and helping. These service robots are intended to coexist with humans and engage in relationships that lead them to a better quality of life in our society. Their constant evolution and the arising of new challenges lead to an update of the existing systems. This update provides a generic vision of two questions: the advance of service robots, and more importantly, how these robots are applied in society (professional and personal) based on the market application. In this update, a new category is proposed: catering robotics. This proposal is based on the technological advances that generate new multidisciplinary application fields and challenges. Waiter robots is an example of the catering robotics. These robotic platforms might have social capacities to interact with the consumer and other robots, and at the same time, might have physical skills to perform complex tasks in professional environments such as restaurants. This paper explains the guidelines to develop a waiter robot, considering aspects such as architecture, interaction, planning, and executionpost-print13305 K