SOURCE-LINKED INTELLIGENCE
ProTracer: Proprioception-Guided Failure Diagnosis in Robot Manipulation
This paper presents a comprehensive framework for robot manipulation failure analysis that includes binary failure detection, failure categorization, explanation generation, and the additional capability of failure onset localization, which aims to identify the earliest moment at which a robot execution deviates from a valid task-completion trajectory and is ultimately followed by task failure. To address these tasks, we propose ProTracer, a training-free framework that leverages existing Vision-Language Models (VLMs) together with proprioceptive signals for failure analysis. Our method uses p
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-18T06:32:27.000Z
First collected: 2026-09-23T14:01:59.594Z. This is not the publication date.