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Training Self-localization Models for Unseen Unfamiliar Places via Teacher-to-Student Data-Free Knowledge Transfer
Rather than relying on the availability of private data of teachers as in existing methods, we propose to exploit an assumption that holds universally in self-localization tasks: "The teacher model is a self-localization system" and to reuse the self-localization system of a teacher as a sole accessible communication channel.
Recursive Distillation for Open-Set Distributed Robot Localization
A typical assumption in state-of-the-art self-localization models is that an annotated training dataset is available for the target workspace.
A Multi-modal Approach to Single-modal Visual Place Classification
Visual place classification from a first-person-view monocular RGB image is a fundamental problem in long-term robot navigation.
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