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The objective of this lab is to advance the state-of-the-art in robotics and autonomous systems, by building systems with the capacity to adapt or learn through interaction with real world environments including humans. The applications that we study are characterised by a need for learning and fusion of information from different sensor modalities. We focus on three major research directions:
Our research methodology is based on developing theoretically sound solutions to real world problems, and places strong emphasis on empirical methods, including use of performance metrics, quantitative comparisons of actual systems, and statistical tests of significance.
Contact person: Tom Duckett
Lab's home page: http://www.aass.oru.se/Research/Learning/