Volume 4, Issue 2 - Special Issue on Assistive Robotics

This paper describes a system integration for a life-sized robot working at a kitchen. On cooking tasks, there should be various tools and foods, and cooking table may have reflective surface with blots and scratch. Recognition functions should be robust to noises derived from them. As other problems, cooking behaviors impose motion sequences by using whole body of the robot. For instance, while cutting a vegetable, the robot has to hold one hand against the vegetable even if another hand with a knife should be moved for the cutting. This motion requires to consider full articulation of the robot simultaneously. That is, we have difficulties against both recognition and motion generation. In this paper we propose recognition functions that are to detect kitchen tools such as containers and cutting boards. These functions are improved to overcome the influence of reflective surface, and combination shape model with task knowledge is also proposed. On the other hand, we pointed out the importance of the use of torso joints while dual arm manipulation. Our approach enables the robot to keep manipulability of both arms and viewing field of a head. Based on these products, we also introduce an integrated system incorporating recognition modules and motion generation modules. The effectiveness of the system was proven through some cooking applications.

Interactive robots are seen as an efficient tool for the improvement of the social communication skills of autistic children. Recent studies show that the effectiveness of the human-robot interaction can be improved further if the robot can provide positive feedback to the child when he/she demonstrates behaviour or social skills as expected. However, there is no clear answer to which visual stimuli and which combination of visual stimuli could attract better attention. In this paper we present initial results from our study of the response of participants with autism traits to four visual stimuli. We conducted a series of experiments where the experimental system provided a visual response to the user’s actions and monitored the user’s performance for each visual stimulus. The experiments were organised as a game and included four groups of participants with different levels of autism. The results showed that a colour tended to be the most effective way for robot interaction with autistic people. The results could help the design of very effective assistive robots for supporting people with autism.

As witnessed in several behavioural studies, a complex relationship exists between people’s cultural background and their general acceptance towards robots. However, very few studies have investigated whether a robot’s original language and gesture based on certain culture have an impact on the people of the different cultures. The purpose of this work is to provide experimental evidence which supports the idea that humans may accept more easily a robot that can adapt to their specific culture. Indeed, improving acceptance and reducing discomfort is fundamental for future deployment of robots as assistive, health-care or companion devices into a society. We conducted a Human- Robot Interaction experiment both in Egypt and in Japan. Human subjects were engaged in a simulated video conference with robots that were greeting and speaking either in Arabic or in Japanese. The subjects completed a questionnaire assessing their preferences and their emotional state, while their spontaneous reactions were recorded in different ways. The results suggest that Egyptians prefer the Arabic robot, while they feel a sense of discomfort when interacting with the Japanese robot; the opposite is also true for the Japanese. These findings confirm the importance of the localisation of a robot in order to improve human acceptance during social human-robot interaction.

A new stream of research and development responds to changes in life expectancy across the world. It includes technologies which enhance well-being of individuals, specifically for older people. The ACCOMPANY project focuses on home companion technologies and issues surrounding technology development for assistive purposes. The project responds to some overlooked aspects of technology design, divided into multiple areas such as empathic and social human-robot interaction, robot learning and memory visualisation, and monitoring persons’ activities at home. To bring these aspects together, a dedicated task is identified to ensure technological integration of these multiple approaches on an existing robotic platform, Care-O-Bot®3 in the context of a smart-home environment utilising a multitude of sensor arrays. Formative and summative evaluation cycles are then used to assess the emerging prototype towards identifying acceptable behaviours and roles for the robot, for example role as a butler or a trainer, while also comparing user requirements to achieved progress. In a novel approach, the project considers ethical concerns and by highlighting principles such as autonomy, independence, enablement, safety and privacy, it embarks on providing a discussion medium where user views on these principles and the existing tension between some of these principles, for example tension between privacy and autonomy over safety, can be captured and considered in design cycles and throughout project developments.

In this paper, we introduce an interactive guide plate system by adopting a gaze-communicative stuffed-toy robot and a gaze-interactive display board. An attached stuffed-toy robot on the system naturally show anthropomorphic guidance corresponding to the user’s gaze orientation. The guidance is presented through gaze-communicative behaviors of the stuffed-toy robot using joint attention and eye-contact reactions to virtually express its own mind in conjunction with b) vocal guidance and c) projection on the guide plate. We adopted our image-based remote gaze-tracking method to detect the user’s gazing orientation. The results from both empirical studies by subjective / objective evaluations and observations of our demonstration experiments in a semipublic space show i) the total operation of the system, ii) the elicitation of user’s interest by gaze behaviors of the robot, and iii) the effectiveness of the gaze-communicative guide adopting the anthropomorphic robot.

The majority of EU citizens report a positive view about robots in general according to recent EU-level survey data. However, does this also hold true for attitudes towards service robots in particular? To investigate this research question, we conducted a survey on a representative sample from Germany. Importantly, we explored the role of demographic variables, interest in science and technology, and personality traits associated with psychological anthropomorphism in determining perceived acceptance of service robots in everyday life. Overall, attitudes towards service robots turned out to be relatively positive. Moreover, demographic variables (e.g., gender, occupation), interest in science and technology, and dispositional correlates of anthropomorphism had a significant impact on attitudes towards such assistive technology.

The analysis of certain parameters related to cognitive and to motor humans’ activities in everyday life conditions can allow to detect potential behavioral troubles, make diagnoses and assess patients’ progress after a therapy. Within this context, personal robots can provide an autonomous movable platform for embedded sensors allowing to detect and track humans while ensuring an optimal observability of the person’s activity in complex and cluttered environments. This paper presents a framework combining a multimodal human detector based on sensors embedded in a mobile robot and a decisional engine exploiting the fuzzy logic mechanisms to make the robot track humans, maximizing observability and facing losses of detection. The robustness of this framework is evaluated experimentally in home spaces through different scenarios. Such a mobile system provides an effective marker-less motion capture means for sensing human activity in non-invasive fashion. We present a physical model based method exploiting the features of the system and of the embedded Kinect. Its performances are evaluated first comparing the results to those obtained with a precise 3D motion capture marker based system and to data obtained from a dynamic posturography platform. Then an experiment in real life conditions is performed to assess the system sensitivity to some gait disturbances.

In the last few decades, bio-robotics applications such as exoskeletons, prosthetics and robotic wheelchairs have progressed from machines in science fiction to nearly commercialized products. Though there are still several challenges associated with electromyography (EMG) signals, the advances in use of EMG signals for controlling such bio-robotics applications have been enormous. Similarly, recent trends and attempts in developing electroencephalography- (EEG) based control methods have shown the potential of this area in the modern bio-robotics field. However, the EEG-based control methods are also yet to be perfected. A new approach of combining both these control methods, which take the advantages, and diminish the disadvantages, of each system might therefore be a promising approach. In this paper, we review hybrid fusion of EMG- and EEG-based control approaches in the bio-robotics field which have been attempted or developed to date. We provide a design overview of the method and consider the main features and merits/disadvantagages for the approaches that have been analyzed. We also discuss the current challenges regarding these hybrid EEG-EMG control approaches and propose some potential future directions.