General-purpose pre-trained models (" foundation models") have enabled practitioners to
produce generalizable solutions for individual machine learning problems with datasets that …

Learning provides a powerful tool for vision-based navigation, but the capabilities of
learning-based policies are constrained by limited training data. If we could combine data …

Machine learning techniques rely on large and diverse datasets for generalization.
Computer vision, natural language processing, and other applications can often reuse …

Machine learning provides a powerful tool for building socially compliant robotic systems
that go beyond simple predictive models of human behavior. By observing and …

Indoor localization is essential for robotic navigation by using different sensors on board.
Specifically, visual localization with a single camera is a great challenge in highly symmetric …

Vision-based topological localization is recently emerging as a promising alternative to
metric pose estimation techniques in robotic navigation systems. Contrarily to the latter …

Target search in unknown environments places high demands not only on an autonomous
vehicle's ability to perceive and interpret target cues, but also on its conscious of collecting …

We present a novel graph memory structure for navigation, called Frontier-enhanced
Topological Memory (FTM). Most prior research primarily focuses on maintaining memory …

Recently, robot navigation methods using human instructions have been actively studied,
including visual language navigation. Although language is one of the most promising forms …

This study presents a control framework leveraging vision language models (VLMs) for
multiple tasks and robots. Notably, existing control methods using VLMs have achieved high …