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Chronos Policy: Learning Robot Policies on Physical Time

Paper recorded by Signals 4 on 2026-10-09 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-09 on arXiv · recorded by Signals 4 on 2026-10-12

Category: cs.CV · 计算机视觉 · first seen 2026-10-12

Abstract

Robot policies often convert sensing and control into fixed-rate observation-action sequences, leaving physical time implicit in sequence position. This assumption breaks when observation rates or delays vary, or when inference latency changes. We introduce Chronos Policy, which makes physical time explicit by conditioning on observation capture times and desired action execution times. We study t

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#294 most recent of 756 cs.CV papers we have recorded · ↑ newer: Images Talk Back: Guiding MMDiTs by Suppressing Image-to-Text Feedback · ↓ older: Can machines reason non-verbally?
Cite this page: Chronos Policy: Learning Robot Policies on Physical Time: the #294 most recent of 756 cs.CV papers we have recorded (as of 2026-10-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/chronos-policy-learning-robot-policies-on-physical-time.html
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