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Telemanipulation in power stations commonly require robots first to open doors and then gain access to a new workspace. However, the opened doors can easily close by disturbances, interrupt the operations, and potentially lead to collision damages. Although existing telemanipulation is a highly efficient master–slave work pattern due to human-in-the-loop control, it is not trivial for a user to specify the optimal measures to guarantee safety. This paper investigates the safety-critical motion planning and control problem to balance robotic safety against manipulation performance during work emergencies. Based on a dynamic workspace released by door-closing, the interactions between the workspace and robot are analyzed using a partially observable Markov decision process, thereby making the balance mechanism executed as belief tree planning. To act the planning, apart from telemanipulation actions, we clarify other three safety-guaranteed actions: on guard, defense and escape for self-protection by estimating collision risk levels to trigger them. Besides, our experiments show that the proposed method is capable of determining multiple solutions for balancing robotic safety and work efficiency during telemanipulation tasks.

For more socially natural interactions between robots and humans there is a need for the robots to detect and understand the current internal state of the individuals they interact with. In this paper, we investigate the impact of personality, user sensory profile, and morningness–eveningness type of an individual on the variation of different physiological parameters (i.e., blinking, galvanic skin response, facial temperature variation), as well as the performance in a non-verbal word-color Stroop task. The TIAGo humanoid robot displayed two interaction styles that are based on visual and auditory stimuli. The visual and auditory stimuli used by the robot are in accordance with the user sensory profile. We report the results of a within participants study carried out with 24 participants. Our results show that personality, user sensory profile, and morningness–eveningness type have an impact on the variation of the chosen physiological parameters. Furthermore, the interaction style of the robot has an influence on the variation of the physiological parameters.

International audience; Creating a convincing affective robot behavior is a challenging task. In this paper, we are trying to coordinate between different modalities of communication: speech, facial expressions, and gestures to make the robot interact with human users in an expressive manner. The proposed system employs videos to induce target emotions in the participants so as to start interactive discussions between each participant and the robot around the content of each video. During each experiment of interaction, the expressive ALICE robot generates an adapted multimodal behavior to the affective content of the video, and the participant evaluates its characteristics at the end of the experiment. This study discusses the multimodality of the robot behavior and its positive effect on the clarity of the emotional content of interaction. Moreover, it provides personality and gender-based evaluations of the emotional ex-pressivity of the generated behavior so as to investigate the way it was perceived by the introverted-extroverted and male-female participants within a human-robot interaction context.

International audience; We design a personalized human-robot environment for social learning for individuals with autism spectrum disorders (ASD). In order to define an individual�s profile, we posit that the individual�s reliance on proprioceptive and kinematic visual cues should affect the way the individual suffering from ASD interacts with a social agent (human/robot/virtual agent). In this paper, we assess the potential link between recognition performances of body/facial expressions of emotion of increasing complexity, emotion recognition on platforms with different visual features (two mini-humanoid robots, a virtual agent, and a human), and proprioceptive and visual cues integration of an individual. First, we describe the design of the EMBODI-EMO database containing videos of controlled body/facial expressions of emotions from various platforms. We explain how we validated this database with typically developed (TD) individuals. Then, we investigate the relationship between emotion recognition and proprioceptive and visual profiles of TD individuals and individuals with ASD. For TD individuals, our results indicate a relationship between profiles and emotion recognition. As expected, we show that TD individuals that rely more heavily on visual cues yield better recognition scores. However, we found that TD individuals relying on proprioception have better recognition scores, going against our hypothesis. Finally, participants with ASD relying more heavily on proprioceptive cues have lower emotion recognition scores on all conditions than participants relying on visual cues.

In social HRI context, the robot’s usefulness and appropriate behavior plays an important role. A robot should be able to understand the human’s internal state (i.e., physiological and psychological states) so as to provide an adaptive and thus efficient assistance within daily life activities. Measuring stress and frustration of an individual while performing a certain task is a critical element that can help the robot adapt its behavior so as to improve user’s interest and task performance and to reduce his/her frustration. In this paper, we designed an experiment called “Stress Game”. In our work, stress is measured in terms of heart rate signal. The robot displays different behaviors as a function of user’s personality and game condition. We conducted our experiments with the NAO robot. The experimental results support our hypotheses that the robot has a positive effect on stress relief.

This paper describes a hands-off socially assistive therapist robot designed to monitor, assist, encourage, and socially interact with post-stroke users engaged in rehabilitation exercises. We investigate the role of the robot’s personality in the hands-off therapy process, focusing on the relationship between the level of extroversion–introversion of the robot and the user. We also demonstrate a behavior adaptation system capable of adjusting its social interaction parameters (e.g., interaction distances/proxemics, speed, and vocal content) toward customized post-stroke rehabilitation therapy based on the user’s personality traits and task performance. Three validation experiment sets are described. The first maps the user’s extroversion–introversion personality dimension to a spectrum of robot therapy styles that range from challenging to nurturing. The second and the third experiments adjust the personality matching dynamically to adapt the robot’s therapy styles based on user personality and performance. The reported results provide first evidence for user preference for personality matching in the assistive domain and demonstrate how the socially assistive robot’s autonomous behavior adaptation to the user’s personality can result in improved human task performance.

Welcome to the Intelligent Service Robotics special issue on Multidisciplinary Collaboration on Socially Assistive Robotics. This special issue tries to address a powerful new trend in robotics research, that of robots getting closer to humans and the need to endow them with the abilities of interaction so that they can be productively integrated into our lives. Human–robot interaction (HRI) for socially assistive applications is still in its infancy, but it is a growing and increasingly popular research area at the intersection of robotics, health science, psychology, social and cognitive sciences. Assistive robotics has the potential to enhance the quality of life for large populations of users. In response to the rapidly growing elderly population, research attention has been turned to the study and development of robot pets, companions and cognitive and mobility aids aimed at reducing stress and depression and maintaining autonomy. In addition, individuals with physical impairments and those in rehabilitation therapy are also potential beneficiaries of socially assistive technologies, not only for improved mobility but also for improved outcomes in recovery. Finally, individuals with cognitive disabilities and developmental and social disorders (e.g., autism) constitute another growing population that could benefit from assistive robotics in the context of special education, therapy and training. An effective socially assistive robotmust understand and interact with its environment, exhibit social behavior and focus its attention and communication on the user to help her/him achieve goals.

Welcome to the Autonomous Robots special issue on the emerging area of Socially Assistive Robotics (SAR). What is SAR? Socially assistive robotics focuses on providing assistance through social rather than physical interaction between the robot and the human user. SAR has the potential to enhance human quality of life for large user populations, including the elderly, people with physical impairments, those involved in rehabilitation therapy (e.g., post-stroke patients), and people with cognitive disabilities and social and developmental disorders (e.g., children with autism spectrum disorder, children with attention deficit/hyperactivity disorder (AD/HD)). Socially assistive robotics has a great variety of potential uses and associated multi-faceted research and usability challenges. Numerous interesting questions and issues need to be addressed as we aim toward including robust, reliable, user-friendly, empathetic, and encouraging robots in our daily lives. Those questions include: “What are the circumstances in which people (especially those with special needs) accept an assistive robot in their environment?” “What modes of communication should the robot employ?” “What is the role of the robot’s physical embodiment?” “How to integrate the a priori knowledge about the users into the robot system?” “How can the human-robot interaction design ensure safety?” and “How are friendly, familiar, usable, and effective interaction models with a robot to be designed?”