4 papers · 1 filter
PoLAR: Factorizing Extent and Mode in Latent Actions for Robot Policy Learning
Youngjoon Jeong, Jihwan Yu, Minsoo Jo +2
Latent action pretraining learns representations of visual change from pairs of observations, but existing methods typically encode each transition as a single unstructured represe…
Uncovering Vulnerability of Vision-Language-Action Models under Joint-Level Physical Faults
Minsoo Jo, Taeju Kwon, Junha Chun +2
Deploying Vision-Language-Action (VLA) models in real robotic systems requires robustness not only to semantic and perceptual variations, but also to embodiment-side faults that ch…
Sparse Imagination for Efficient Visual World Model Planning
Junha Chun, Youngjoon Jeong, Taesup Kim
World model based planning has significantly improved decision-making in complex environments by enabling agents to simulate future states and make informed choices. This computati…
Learning to Act Robustly with View-Invariant Latent Actions
Youngjoon Jeong, Junha Chun, Taesup Kim
Vision-based robotic policies often struggle with even minor viewpoint changes, underscoring the need for view-invariant visual representations. This challenge becomes more pronoun…