用协调契约实现机器人双臂任务的保守干预，提升决策安全性
CoWAM: Coordination Contracts for Selective Policy Intervention with WAMs
- 将同步、角色兼容、碰撞收敛定义为可验证的协调契约
- 在8个模拟任务中比基线提升9.6%成功率，误干预率低于1%
- 适合需要安全、可控干预的双臂协作机器人场景
世界动作模型（WAMs）通过动作条件预测未来来增强机器人策略，但仅凭合理未来不足以支持改变双臂策略的动作。本文提出CoWAM，一种选择性干预层，将同步性、角色兼容性和碰撞收敛性表达为协调契约。每个契约结合类型合法性检查、事件触发验证和校准的干预门控机制。只有当替代动作满足所有活跃义务且带来明确低风险改进时，才保留原动作；若原动作也不合法，则启用预设的放弃备选方案。为分离选择器质量与提议质量，所有方法在相同候选池上运行，并在共享标注前做出决策。在八个模拟双臂任务中，CoWAM相比仅使用契约的变体，协调有效选择率提升16.7个百分点，闭环成功率较最强选择性基线提升9.6个百分点，同时有害干预比例保持在1%以下。结果表明，协调契约是处理高协同性双臂任务中保守策略干预的有效接口。
原文摘要 · Abstract (English)
World Action Models (WAMs) augment robot policies with action-conditioned predicted futures, but a plausible future alone does not justify changing the action that a bimanual policy would execute. We present CoWAM, a selective intervention layer that expresses synchronization, role compatibility, and collision convergence as coordination contracts. Each contract combines typed admissibility checks with event-conditioned verification and calibrated intervention gates. CoWAM preserves the nominal action unless an alternative satisfies every active obligation and provides a clear, low-risk improvement; when the nominal action is also inadmissible, it invokes a predefined abstention fallback. To separate selector quality from proposal quality, all methods operate on identical candidate pools and commit their decisions before shared oracle labeling. Across eight simulated bimanual tasks, CoWAM improves coordination-valid selection by 16.7 percentage points over the contract-only variant and raises closed-loop success by 9.6 percentage points over the strongest selective baseline, while keeping harmful interventions below 1%. Together, these results establish coordination contracts as an effective interface for conservative policy intervention with predicted world-action evidence across coordination-rich bimanual tasks.
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