DREAMProject reference: 611391
Funded under :
Development of Robot-Enhanced therapy for children with AutisM spectrum disorders
Total cost:EUR 8 721 727
EU contribution:EUR 6 690 000
Call for proposal:FP7-ICT-2013-10See other projects for this call
Funding scheme:CP - Collaborative project (generic)
In clinical interventions, skill transfer from therapist to children with autism spectrum disorders (ASD) benefits from the inclusion of expressive artefacts such as puppets and animated characters. Well-designed robotic agents have proven to be particularly effective and are becoming an increasingly important tool for mediating between therapists and ASD children in robot-assisted therapy (RAT). However, therapeutic interventions require significant human resources over extended periods. Consequently, to make a significant difference, therapeutic robots need to have a greater degree of autonomy than current remote-controlled systems. Furthermore, they have to act on more than just the child's directly-observable movements because emotions and intentions are even more important for selecting effective therapeutic responses.\n\n\nThe next generation of RAT, which we refer to as robot-enhanced therapy (RET), will be able to infer the ASD children's psychological disposition and assess their behaviour in order to select therapeutic actions. Since children require therapy tailored to individual needs RET robots will provide this too. Driven by therapists, DREAM will deliver next-generation RET, developing clinical interactive capacities for supervised autonomy therapeutic robots; robots that can operate autonomously for limited periods under the supervision of a therapist. The DREAM robot will also function as a diagnostic tool by collecting clinical data on the patient. It will operate under strict ethical rules and the DREAM project will provide policy guidelines to govern ethically-compliant deployment of supervised autonomy RET.\n\n\nThe core of the DREAM RET robot is its cognitive model which interprets sensory data (body movement and emotion appearance cues), uses these percepts to assess the child's behaviour by learning to map them to therapist-specified behavioural classes, and then learns to map these child behaviours to appropriate therapist-specified robot actions.