Project description
Robots to promote physical communication during handwriting and music learning
Neuroscientific research has demonstrated the benefits of physical interaction in learning complex sensorimotor tasks. The human central nervous system recognises a partner's motor control and can use it to increase work execution and motor learning. The EU-funded CONBOTS project will investigate a paradigm shift that promotes physical communication mediated by robots to enhance handwriting in children and music learning in beginner musicians. The project will apply innovative robotic technology, wearable sensors and machine learning algorithms to establish a physically interactive robotic platform that will connect humans to support the learning of complex sensorimotor tasks. The results of the project will advance the use of robotics in the education field.
Objective
From a parent coordinating movements to help a child learn to walk, to a violinist training a concerto, humans rely on physical interaction to learn from each other and from the environment. Building on a strongly multidisciplinary foundation with an integrated approach, CONBOTS proposes a paradigm shift that aims to augment handwriting and music learning through robotics, by creating a physically interacting robotic platform connecting humans in order to facilitate the learning of complex sensorimotor tasks.
The newly designed platform will combine four enabling technologies: i) compact robotic haptic devices to gently interact with upper limbs; ii) an interactive controller yielding physical communication, integrating differential Game Theory (GT) and an algorithm to identify the partner’s control; iii) a bi-directional user interface encompassing AR-based application-driven serious games, and a set of wearable sensors and instrumented objects; iv) Machine learning algorithms for tailoring learning exercises to the user physical, emotional, and mental state
CONBOTS is building on recent neuroscientific findings that showed the benefits of physical interaction to performing motor tasks together, where the human central nervous system understands a partner motor control and can use it to improve task performance and motor learning. This will be implemented on innovative robotic technology, wearable sensors and machine learning techniques to give rise to novel human-human and human-robot interaction paradigms applied in two different learning contexts: i) training graphomotor skills in children learning handwriting; ii) augmenting learning performance in beginner musicians.
Using its neuroscience-driven unifying approach to motor learning and physical communication CONBOTS will expand the impact and the application of robotics to the education industry.
Fields of science
- natural sciencesbiological sciencesneurobiology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencesmathematicsapplied mathematicsgame theory
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringrobotics
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Keywords
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
NE1 7RU Newcastle Upon Tyne
United Kingdom