# HIRE：面向视觉混淆精密操作的历史条件交互推理与高频执行

> 原文链接：https://robotics.hellobike.com/papers/2026-09-25-2609-30828
> 频道：papers | 更新日期：2026-09-25 | 标签：arxiv, cs.RO
> 核心摘要：HIRE通过历史条件交互状态推理与高频执行，解决接触关键精密操作的视觉歧义，并在真实机器人表面、插入和旋转交互中验证。

# HIRE：面向视觉混淆精密操作的历史条件交互推理与高频执行

::: v-pre
> 原文链接：[HIRE: History-Conditioned Interaction Reasoning and High-Rate Execution for Visually Aliased Precision Manipulation](https://arxiv.org/abs/2609.30828)（arXiv 2609.30828 · 发布日期：2026-09-25）

**HIRE: History-Conditioned Interaction Reasoning and High-Rate Execution for Visually Aliased Precision Manipulation**

HIRE通过历史条件交互状态推理与高频执行，解决接触关键精密操作的视觉歧义，并在真实机器人表面、插入和旋转交互中验证。

## 核心要点

- 接触关键精密操作具有历史依赖，视觉相似观测可能对应不同潜在交互状态，当前视觉策略难以消歧。
- HIRE采用跨频率框架，ISR编码有序力/力矩历史作为持续物理证据，IME分解内在进展与横向校正。
- 真实机器人表面、插入和旋转交互实验中，所有评估阶段完成率至少90%，并提升状态消歧、执行精度与泛化。
- 代码将在论文发表时发布。

**验证范围与局限**：验证范围为真实机器人上的表面、插入和旋转交互任务。

## 英文摘要 (Abstract)

Precision manipulation with contact-critical interactions is often history-dependent: visually similar observations can correspond to different latent interaction states and therefore require different actions, while small execution errors can alter task outcomes. Policies relying on the current visual observation alone cannot resolve such ambiguity; force-aware and memory-augmented methods enrich physical or temporal context, while reactive high-rate policies improve local contact response, yet long-horizon temporal reasoning and precision execution remain largely decoupled in existing methods, limiting reliable progression in visually aliased precision manipulation. To bridge this gap, we introduce History-Conditioned Interaction Reasoning and Execution (HIRE), a cross-rate framework comprising a history-conditioned Interaction-State Reasoner (ISR) and a high-rate Interaction-Manifold Executor (IME). ISR encodes ordered wrench history with a temporal wrench encoder and Force Perceiver as persistent physical evidence for state-consistent action generation, while IME structures contact-critical motion into intrinsic progress and transverse correction for precise execution; their cross-rate loop allows the resulting physical traces to inform subsequent reasoning. In real-robot experiments across surface, insertion, and rotational interactions, HIRE achieves at least 90% completion across all evaluated task stages while improving interaction-state disambiguation, execution precision, and generalization. More broadly, HIRE provides a unified reasoning--execution perspective on precision manipulation under history-dependent partial observability, where physical interaction both realizes task intent and reveals latent-state evidence for future decisions. Code will be released upon publication.

作者：Rongji Li, Wenhao He, Cewu Lu, Xingyu Chen, Xu-Yao Zhang
:::

## 原始参考来源 (Sources)

- [arXiv 2609.30828：HIRE: History-Conditioned Interaction Reasoning and High-Rate Execution for Visually Aliased Precision Manipulation](https://arxiv.org/abs/2609.30828)