3 accepted papers
The synthesis of realistic Martian landscape videos, essential for mission rehearsal and robotic simulation, presents unique challenges. These primarily stem from the scarcity of high-quality Martian data and the significant domain gap relative to terrestrial imagery. To address these challenges, we…
Vision-Language-Action (VLA) models, pre-trained on large-scale imitation learning datasets, have demonstrated remarkable capabilities in visuomotor control. However, these models exhibit diverse failure modes in unstructured real-world environments, limiting the widespread adoption of VLAs in robot…
Foundation models, e.g., large language models (LLMs), trained on internet-scale data possess zero-shot generalization capabilities that make them a promising technology towards detecting and mitigating out-of-distribution failure modes of robotic systems. Fully realizing this promise, however, pose…