# GuideFetch：用于辅助机器狗并发导航与物体取回的任务协调框架

> 原文链接：https://robotics.hellobike.com/papers/2026-08-18-2608-18292
> 频道：papers | 更新日期：2026-08-18 | 标签：arxiv, cs.RO
> 核心摘要：GuideFetch用LLM生成受日程约束的动作方案，协调异构机器狗导盲与取物，并在仿真中验证。

# GuideFetch：用于辅助机器狗并发导航与物体取回的任务协调框架

::: v-pre
> 原文链接：[GuideFetch: A Task Coordination Framework for Concurrent Navigation and Object Retrieval in Assistive Robot Dogs](https://arxiv.org/abs/2608.18292)（arXiv 2608.18292 · 发布日期：2026-08-18）

**GuideFetch: A Task Coordination Framework for Concurrent Navigation and Object Retrieval in Assistive Robot Dogs**

GuideFetch用LLM生成受日程约束的动作方案，协调异构机器狗导盲与取物，并在仿真中验证。

## 核心要点

- 面向一只导盲护送用户就座、另一只取送物体的并发协作任务。
- LLM实例化四动作模式，归一化与校验约束目标、能力和日程。
- 360次仿真中，在线计划均首请求通过验证并匹配脚本参考。
- 顺序与并行分别成功72/90、71/90；共同成功中并行平均耗时降41.3%。

**验证范围与局限**：验证范围为90个场景-种子组合的仿真运行，以及不含仿真的突变测试。

## 英文摘要 (Abstract)

Consider one robot guide dog escorting a blind user to a seat while a second retrieves and delivers an object. We introduce \textsc{GuideFetch}, a framework for coordinating this concurrent guide-and-fetch mission with heterogeneous robots. A large language model (LLM) instantiates a schedule-conditioned four-action schema; deterministic normalization and validation enforce registered targets, robot capabilities, and the selected schedule, while robot and object states govern execution and completion. We record 360 simulator runs over 90 scene--seed combinations under scripted and online plan-provenance conditions. All 180 online responses validate on the first request and match their scripted references, so the plan-provenance comparison tests normalized-plan agreement rather than a distinct execution factor. A simulator-free mutation test accepts two valid controls and rejects all 32 rule-violating variants. Across 90 scene--seed cases per schedule, sequential and parallel execution achieve $72/90$ and $71/90$ operational successes. Among 56 common successes, the implemented role-reassigned parallel protocol reduces mean makespan by 41.3\%. This system-level gain combines role assignment, action overlap, and scene geometry; state checks distinguish plan validity from verified mission completion.

作者：Qian Yin, Ruiping Liu, Kunyu Peng, Jianxiang Man, Isik Baran Sandan, Junwei Zheng, Yufan Chen, Di Wen, Kailun Yang, Rainer Stiefelhagen
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## 原始参考来源 (Sources)

- [arXiv 2608.18292：GuideFetch: A Task Coordination Framework for Concurrent Navigation and Object Retrieval in Assistive Robot Dogs](https://arxiv.org/abs/2608.18292)