接触密集操作总在碰坏了才发现问题？ContactGuard 在接触前看潜在视觉嵌入提前判断，能直接发中止信号，不用改策略。
ContactGuard 是一种用于分块视觉运动策略的接触前执行监控方法。它根据策略规划的动作块，在潜在视觉空间预测短期后果，若预测失败则中止执行。其潜在世界模型由未标注机器人轨迹训练，预测多视角视觉嵌入，避免像素级视频预测。在真实接触密集操作任务中，ContactGuard 比直接预测和破坏动作消融的失败预测更准确。该方法可作为真机预接触中止信号，无需修改底层策略。
ContactGuard: Pre-Contact Execution Monitoring with Action-Conditioned Latent World Models
Contact-rich manipulation failures are often detected only after the robot has committed to contact. This is especially limiting in wrist-camera setups: close gripper--object views help observe contact, but a poor approach may already push, miss, slip, or disturb the object before conventional detectors react. We introduce \emph{ContactGuard}, a pre-contact execution monitor for chunked visuomotor policies. Given the policy's planned action chunk, ContactGuard predicts its short-horizon consequence in latent visual space and aborts if the predicted future latent indicates likely failure. Its latent world model is trained from unlabelled robot trajectories to predict compact multi-view visual embeddings under planned actions, avoiding pixel-level video prediction. A lightweight failure probe is then trained from a small labelled set of pre-contact clips. At deployment, ContactGuard anchors prediction before an imminent contact event, rolls the model forward under the policy's own actions, and verifies the predicted post-contact latent. Across real-world contact-rich manipulation tasks, ContactGuard predicts failure more accurately than direct and corrupted-action ablations, and transfers to live robot as a pre-contact abort signal without modifying the underlying policy.