Fundamentals for Motor Control of Robotic Augmentation

Lead Research Organisation: University of Cambridge
Department Name: MRC Cognition and Brain Sciences Unit

Abstract

AUGMENT is centred around the unique challenge of controlling motor augmentation technology. We are witnessing the rise of a novel class of technologies, designed to resemble human limbs in their functionalities. These extra fingers and arms are robotic devices that are designed to extend the user's motor capabilities (hereafter X-devices). Beyond the traditional substitution of missing functions, X-devices can be further exploited to provide additional motor functions to already fully functional individuals. But what cognitive and physiological resources could we utilise to control extra limbs, in addition to our own? The goal of AUGMENT is to harness basic understanding of human motor learning and control to guide successful technological development of X-devices in abled and disabled individuals. An urgent question is how to provide motor commands and somatosensory feedback to and from the X-device without restricting the cognitive and motor control of the biological limbs. I will address this by first identifying the neurocognitive mechanisms best suited for successful X-devices motor control. Then I will investigate the optimal integration of somatosensory information from the X-device to afford intuitive and transferable motor skill learning. Finally, I will provide innovative solutions for increasing the functionality of disabled individuals in daily life, beyond traditional substitution, using novel X-devices. By identifying and solving the fundamental sensorimotor human-device interface challenges across diverse user groups and functional needs, AUGMENT will be crucial for the realisation of motor augmentation and other related technologies that aim to put the user at the centre of robot control, design and development.

Publications

10 25 50