Social Robots and Sensors

Dear Colleagues,

The inclusion of robots in daily life environments, where they interact and cooperate with people in solving everyday tasks, has become a reality in the last years. Stepping from controlled environments and predefined tasks to these open scenarios causes many challenges, but the huge potential of these new application domains has driven an important effort towards overcoming them. Hence, robots are becoming significantly more aware, cooperative, autonomous, cognitive, interactive, adaptive, and/or proactive. They can adapt to new manufacturing processes using learning from demonstration, cooperate with human workers through stigmergy, or directly share attention and actions, engage people in social interactions to propose activities or share information, drive exercises in rehabilitation therapies, become natural and intuitive interfaces between a smart environment and its users, or act as social facilitators in public scenarios such as retirement houses or museums. Moreover, these new robots are flexible and adaptable enough to achieve not one but many of these functionalities using only one platform with minimal (if any) hardware changes.

Many of the new market domains identified for robots (e.g. in the EU report ‘Robotics 2020 multi-annual roadmap for robotics in Europe’) require robots to exhibit social abilities. A social robot is an agent included in a heterogeneous environment in which it can perceive, interact with, and learn from people, other robots, and the environment itself. Such an agent needs to be endowed, among other features, with a carefully co-designed appearance and functionality, that eases acceptability and utility, a versatile and powerful cognitive architecture, a set of actuators that guarantee safe operation, and a set of sensors that provide the robot with all data required by its perceptive and cognitive systems.

New sensors are being developed to match the requirements of social robots in terms of dimensions, energy consumption, functionality and adaptability. Some examples are embedded small-size vision systems including one or more cameras, or flexible distributed low-cost haptic sensors. On the other hand, many sensors for social robots are adopted from other research or market fields. RGB-D devices are probably one of the best examples of this process, but the same applies to haptic sensors, voice detection and recognition systems, or LIDAR devices for navigation. It is in the adaptation of these devices to the context of social robotics that the interest lies, as well as in the use of sensor fusion techniques to merge data streams coming from different sensors into a common representation. The fusion of multiple sensory inputs is not only desirable for social robots in terms of increasing their perceptual capabilities and robustness, it is also a key requirement for robots that must maximize acceptability and utility for sometimes untrained users. For example, a socially assistive robot working with elderly people will benefit from offering multimodal interaction channels (e.g. audio, gestures, tactile screens, etc.), to ease accessibility for the wider range of users despite their possible impairments or interaction preferences.

The Special Issue “Social Robots and Sensors” aims to offer a detailed view of the state of the art of the research and the technology on sensors for social robots. Special attention will also be given to the sensor fusion approaches and co-design procedures that are devoted to making these agents useful, friendly and accessible devices in the daily life environments of the near future. Therefore, the Special Issue is open to studies on the integration of sensor devices and perceived data with the software architecture of the social robot, data management and fusion. Reasoning and decision-making capabilities based on sensory inputs and their relationship with actuators through the robotic cognitive architecture is also a key topic of this Special Issue.

Dr. Juan Pedro Bandera
Dr. Rebeca Marfil
Dr. Fernando Fernandez Rebollo
Guest Editors

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• social robots 
• artificial vision 
• embedded perceptual systems 
• conversational systems 
• human activity recognition 
• human–robot joint attention 
• biologically inspired sensors
• sensor fusion 
• haptic sensors
• social navigation 
• social robots and IoT 
• integration of sensing, reasoning and action 
• sensing, cognition and decision making