3 accepted papers
Visual object navigation, requiring agents to locate target objects in novel environments through egocentric visual observation, remains a critical challenge in Embodied AI. We propose FEG-VON, a training-free framework that constructs and maintains a Frontier Embedding Graph for efficient Visual Ob
The value of roadside perception which could extend the boundaries of autonomous driving and traffic management has gradually become more prominent and acknowledged in recent years. However existing roadside perception approaches only focus on the single-infrastructure sensor system which cannot rea…
Legged navigation is typically examined within open-world, off-road, and challenging environments. In these scenarios, estimating external disturbances requires a complex synthesis of multi-modal information. This underlines a major limitation in existing works that primarily focus on avoiding obsta…