为机器人操作动作提供可验证的正确性规范，确保语义、因果和可行性三重达标。
The Law of Task-Achieving Body Motion: Axiomatizing Success of Robot Manipulation Actions
- 构建任务-环境-本体（TEE）类，用语义数字孪生建模世界状态
- 将任务达成分解为满足请求、引发因果、可执行三个可验证谓词
- 支持跨平台动作验证与失败归因，适用于厨房容器操作场景
自主代理在执行日常操作任务时，需确保其身体运动在语义上符合任务要求，在环境中具有因果有效性，并在其本体条件下可行。为使机器人能够验证这些属性，本文提出「任务达成身体运动定律」，作为身体运动的公理化正确性规范。为此引入限定范围的任务-环境-本体（TEE）类，将世界状态表示为语义数字孪生（SDT），并定义适用的物理模型，将任务达成分解为三个谓词：满足请求（SatisfiesRequest）——在SDT状态演化中满足语义请求；引发因果（Causes）——在限定物理模型下具备因果充分性；可执行（CanPerform）——在本体层面进行安全与可行性验证。该分解形成可复用、实现无关的接口，支持运动合成与给定身体运动的验证，同时支持类型化故障诊断（语义、因果、本体及超出范围）、跨机器人与环境的可行性分析，以及关于机器人身体运动的反事实推理。我们通过在三种不同移动操作平台上实例化该定律，演示了其在厨房环境中操作带柄容器的实际可用性。
原文摘要 · Abstract (English)
Autonomous agents that perform everyday manipulation actions need to ensure that their body motions are semantically correct with respect to a task request, causally effective within their environment, and feasible for their embodiment. In order to enable robots to verify these properties, we introduce the Law of Task-Achieving Body Motion as an axiomatic correctness specification for body motions. To that end we introduce scoped Task-Environment-Embodiment (TEE) classes that represent world states as Semantic Digital Twins (SDTs) and define applicable physics models to decompose task achievement into three predicates: SatisfiesRequest for semantic request satisfaction over SDT state evolution; Causes for causal sufficiency under the scoped physics model; and CanPerform for safety and feasibility verification at the embodiment level. This decomposition yields a reusable, implementation-independent interface that supports motion synthesis and the verification of given body motions. It also supports typed failure diagnosis (semantic, causal, embodiment and out-of-scope), feasibility across robots and environments, and counterfactual reasoning about robot body motions. We demonstrate the usability of the law in practice by instantiating it for articulated container manipulation in kitchen environments on three contrasting mobile manipulation platforms
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