Explainable AI for Robot Control
Knowledge Generation and Evolution in Intelligent Robots
For autonomous mobile robots, self-localisation and path planning are essential. SLAM (Simultaneous Localisation and Mapping) is a key technology for this purpose, but discrepancies between input information and spatial relationships can cause serious problems. Our laboratory focuses on perceptual aliasing, in which different situations are incorrectly recognised as the same due to incomplete perceptual information, and works on resolving such cognitive discrepancies by drawing on insights from neuroscience.
In particular, our faculty member has worked with Professor Will N. Browne at Queensland University of Technology to improve the performance of XCS Classifier Systems, an evolutionary machine learning method, and to apply them to robot navigation.