arXiv — NLP / Computation & Language · · 3 min read

Agent as Policy for Robotic Manipulation

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Computer Science > Computation and Language

arXiv:2609.12541 (cs)
[Submitted on 11 Sep 2026]

Title:Agent as Policy for Robotic Manipulation

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Abstract:We demonstrate that a general-purpose agent can directly drive a physical robot throughout task execution without any task-specific or environment-specific training. We introduce Agent as Policy (AGP), which places task planning and execution under the agent's control. Given a task and a robot interface, the agent interprets visual evidence, writes executable programs, issues motion commands, and revises its actions in response to physical outcomes. This brings the agent's reasoning and programming capabilities into continuous interaction with the physical world. We study AGP across multiple real-world manipulation tasks spanning precision manipulation, dynamic motions, and deformable objects. These include assembly from human videos, block construction from goal images, die reorientation, targeted throwing, and bimanual towel folding. AGP achieves success rates of 100%, 100%, and 80% on three block construction configurations. These findings establish a path for general-purpose agents to act as robotic policies, extending their autonomy to physical manipulation through runtime reasoning, programming, and interaction.
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2609.12541 [cs.CL]
  (or arXiv:2609.12541v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2609.12541
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Mengzhao Jia [view email]
[v1] Fri, 11 Sep 2026 07:51:39 UTC (36,102 KB)
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