Chronos Policy: Learning Robot Policies on Physical Time
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 two ways to incorporate time into a diffusion transformer: adding timestamp embeddings to token features, or encoding physical time in positional encoding through time-aware rotary positional encodings (time-aware RoPE). We find that time-aware RoPE is more robust, allowing attention to depend dir...
| Authors | Changhao Wang, Jaden Clark, Shuran Song |
|---|---|
| Primary category | cs.RO |
| Published | 9 October 2026 |
| Last updated at source | 9 October 2026 |
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