---
id: 20260505-T0-06
title: "机器人不再“手残”：新方法让视觉语言模型边想边看边操作"
title_en: "New Method Enables Robots to Interleave Text and Image Reasoning in Tasks"
url: https://ai.daily.yangsir.net/daily/20260505-T0-06
issue_date: 2026-05-05
publish_date: 2026-05-04T04:00:00.000Z
category: research
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2605.00438
---

# 机器人不再“手残”：新方法让视觉语言模型边想边看边操作

机器人执行长期操作任务时，需要逻辑连贯且基于空间几何的规划。当前的视觉-语言-动作模型通常将规划隐藏在潜在状态中，或仅输出纯文本的思考链，导致几何信息丢失，难以完成复杂操作。研究人员提出了一种交错视觉与语言的推理轨迹方法。该方法使模型能够在推理过程中同时生成文本和图像进行多模态思考，直接将逻辑与几何对齐，从而显著提升了机器人在长时间跨度下的操作成功率。

## English Version

**New Method Enables Robots to Interleave Text and Image Reasoning in Tasks**

Current Vision-Language-Action models struggle with long-horizon robotic manipulation because they rely on latent states or text-only reasoning, losing geometric grounding. This research introduces interleaved vision-language reasoning traces, allowing models to process both text and images during planning. This method aligns logic with geometry directly, improving task success rates.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2605.00438)

**详情页**：https://ai.daily.yangsir.net/daily/20260505-T0-06

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