SOCRATES is a training program for 15 PhD students,
created to develop the field of Social Robotics with an application focus on
Robotics in Eldercare.
The heart and soul of SOCRATES was our 15 PhD students! To support them and their training, a consortium comprising seven universities/research institutes, three industrial partners, two end-user oriented partners, and three business oriented organisations was formed. More information in the ABOUT menu above.
The research in Social Robotics has a common theme of Interaction Quality, which is a concept for characterization of how a specific mode of interaction is fit for a given task, situation, and user. Interaction Quality often changes, for instance if an older adult gets tired and loses focus when interacting with a robot. Interaction Quality also depends on the robot’s functionality and design. By slowing down the speed of the robot, Interaction Quality can be maintained. In general, Interaction Quality is a complex interplay between several performance measures and design parameters. In SOCRATES we address these issues from a range of perspectives in five research workpackages (more information can be found in the RESEARCH menu above):
- Emotion: novel multi-modal methods to perceive human emotions from facial expressions, body motion, auditory and language cues
- Intention: new techniques to infer human goals and intention from natural language and video analysis
- Adaptivity: techniques to adapt a robot’s behaviour to user needs
- Design: Novel design methods for hardware, interfaces, and safety
- Acceptance: Procedures for evaluation of user acceptance
Additional value and impact is generated by the unique multidisciplinary collaboration between academic disciplines that normally do not work together; computer science, cognitive science, biomechanics, ethics, social psychology, and social science. Intersectoral collaboration between academia, caregivers, business developers, and robot manufacturers will further strengthen novelty and impact by ensuring that relevant needs are addressed, and that research result are both economically and technically feasible.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 721619
