Sensing for Social Robots
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".
Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 11848
Special Issue Editors
Interests: social robotics; human–robot interaction; architectural aspects of robotics, including robot modeling and control; networked and cooperative robotics; system integration
Special Issue Information
Dear colleagues,
Social robots are getting ubiquitous, posing growing pressure on the robotics community to deliver these artificial entities able to play interesting roles in society. Robot skills are, slowly but surely, approaching humans’, i.e., to mimic and further extend humans’ typical skills. Hence, in addition to sensing matching human senses, there is a drive to develop novel sensors and processing techniques for the data produced.
The challenges for the sensors community are huge, ranging from materials to operation principles, mathematical models, sensor fusion, perception, and artificial intelligence, as well as hardware and software aspects. The need to estimate both concepts related to social sciences, e.g., emotions, and well-defined indicators, e.g., touch position and pressure, odors, and localization, is representative of the variety of sensor fields involved. In addition, networked social robotics extends the possibilities of sensor architectures. The dependability of robotics systems is affected by uncertainties typically present in social scenarios. Sensor uncertainties may even remain in the background of those intrinsic to social concepts, not affecting prospective robot skills. The importance of sensing in the context of social robots is thus clear.
This Special Issue aims at highlighting the current panorama and gathering novel ideas emerging in this exciting field.
Dr. João Silva Sequeira
Dr. Rodrigo Ventura
Guest Editors
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Keywords
- social robots
- sensor uncertainties
- perception
- sensor fusion
- sensor modeling
- sensor networking
- human senses
- sensor dependability
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