Cortically inspired sensor fusion network for mobile robot egomotion estimation
A cortically inspired sensor fusion network for robotic applications is introduced. Distributed graphical network, with combined feed-forward and recurrent connectivity. No global supervisor, only local processing, storage and exchange of information. Given sensory data, network relaxes into the best explanation of an underlying cause. Extensible to learn sensor correlations and adapt connectivity from incoming data.
sensor fusion mobile robots egomotion estimation cortically inspired network