Despite the impressive developments in neuroscience research over the past decades, we do not yet fully understand how our brains enable us to recognize objects and actions, how we learn, how we plan, or how we use language. A better understanding of brain function and cognition will not only help us manage neurological and psychiatric diseases, but it will also allow us to develop new systems, devices or robots that will interact with humans in a natural and cognitively-compatible way. On other grounds, multi-robot systems pose several interesting problems concerning distributed control and perception, or the emergence of complex behaviors, for which bio-inspired solutions, adequately mold by system theory, are a key factor. In this scope, the interplay between life sciences and engineering is critical as it opens up new avenues both for scientific research as well as for the design of new applications with a clear societal impact.
RBCog-PhD focuses on the multidisciplinary use of robotics and neuroimaging, with the twin goals
Imaging techniques have become fundamental tools in the study of brain function, allowing ever more powerful insights into the mechanisms of cognition. However, both image acquisition and analysis face tremendous challenges that need to be overcome as we deepen our understanding of the brain. The areas covered include: novel magnetic resonance imaging (MRI) methods for the study of brain function; particularly multimodal integration of electroencephalogram (EEG) and functional fMRI; and associated signal and image processing methodologies.
The massive deployment of robotic devices in offices, homes and urban environments places the interpretation of human activity and the interaction with humans in a central role. This challenge opens a new landscape of multidisciplinary research in learning, action recognition and cognition, with the ultimate goal of designing human(oid) cognitive companions. The areas covered include: sensorimotor coordination, multisensory fusion, attention, human gesture recognition, uncertainty modelling, and learning from demonstration.
Recent advances in robotics, computer vision, artificial intelligence, statistical signal processing and control theory, as well as the advent of miniaturized sensors and actuators, powerful embedded processors and wireless communication, have afforded the development of networks of autonomous robots and systems. The applications include monitoring and operations in hazardous or remote environments, civil engineering structures and services. The areas covered include the design of biologically inspired socially aware robots.
The call for the 2015 edition is open between November 20th 2015 and December 6th 2015, at 17:00 GMT. See more information in the Applications section.