Advances in Social Robots

Dear Colleagues,

The examples of robotic systems that are available nowadays show automatic systems that perform tasks with a low level of complexity, engaging in dialogue when replying to simple questions and may exploit, with limited awareness, their embodiment.

New technologies demonstrate the possibility to increase the capability of autonomous systems, enabling machines to integrate and collaborate with people in a natural and comfortable way. To process the vast wealth of information that a cyberphysical system receives, effective solutions have to be conceived. Sources of information include sensors that capture information about the environment to act and properly detect the effect of the actions of such systems; cameras acquiring information mainly oriented for human–robot interaction; and body sensors describing the status of the parts composing the robot itself. The proper filtering and processing of relevant information require multiple tasks that cooperate while they act independently. The desired capabilities of social robots range from cognitive processes, problem-solving capability, managing emotions, creativity, and smooth interactions with humans while abiding by ethical rules.

The new and challenging possibilities of robotic companions in society hinge on the proposal and actuation of new, brave, and in some cases, disruptive, solutions in the field of providing the autonomy to act, a deeper understanding of the environment and the interactions with the other actors, and a proactiveness in the tasks to be executed.

This Special Issue on Social Robotics is aimed at academic and industrial researchers who are applying new methods to solve the challenges in the field. The key areas of this Special Issue include, but are not limited to:

cognitive architectures; robot localization and mapping; ethics in robotics; planning; robot awareness; robot cooperation; affective computing; rehabilitation robots; robot therapy; surgical assistants; biologically inspired robotics; deep learning for robotics; intelligent environment

Dr. Filippo Vella
Guest Editor

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