Towards the Harness of Embodied Agents

arXiv cs.AI Papers

Summary

Presents Thea, a harness for embodied agents that orchestrates robot capabilities as callable tools, introducing Scene Graph as Context and Evaluation as Exit Codes to close the loop between agent and physical world.

arXiv:2608.11246v1 Announce Type: new Abstract: The success of coding agents has established the harness as a paradigm: what an agent achieves depends not on the model alone, but on the infrastructure around it. We ask whether the same paradigm extends to embodied agents in the physical world. We present Thea, a harness in which an agentic loop orchestrates robot capabilities, each wrapped as a callable tool. It inherits the core components of coding agents, modified as the physical world requires. The world, however, withholds two abilities that software grants for free: reading the state of the world, and judging the outcome of an action. To bridge these gaps, Thea introduces Scene Graph as Context, a persistent, symbolic representation of the world, and Evaluation as Exit Codes, which detects when an action should terminate, judges whether it succeeded, and on failure diagnoses the cause. Together they close the loop between the agent and the physical world. Rich behaviors then emerge from the composition of tools, and the closed loop carries long-horizon tasks to completion in real environments.
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# Towards the Harness of Embodied Agents
Source: [https://arxiv.org/abs/2608.11246](https://arxiv.org/abs/2608.11246)
[View PDF](https://arxiv.org/pdf/2608.11246)

> Abstract:The success of coding agents has established the harness as a paradigm: what an agent achieves depends not on the model alone, but on the infrastructure around it\. We ask whether the same paradigm extends to embodied agents in the physical world\. We present Thea, a harness in which an agentic loop orchestrates robot capabilities, each wrapped as a callable tool\. It inherits the core components of coding agents, modified as the physical world requires\. The world, however, withholds two abilities that software grants for free: reading the state of the world, and judging the outcome of an action\. To bridge these gaps, Thea introduces Scene Graph as Context, a persistent, symbolic representation of the world, and Evaluation as Exit Codes, which detects when an action should terminate, judges whether it succeeded, and on failure diagnoses the cause\. Together they close the loop between the agent and the physical world\. Rich behaviors then emerge from the composition of tools, and the closed loop carries long\-horizon tasks to completion in real environments\.

## Submission history

From: Wentao Zhu \[[view email](https://arxiv.org/show-email/cfaa6cfa/2608.11246)\] **\[v1\]**Mon, 3 Aug 2026 09:19:38 UTC \(2,645 KB\)

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