QuadAgent: A Responsive Agent System for Vision-Language Guided Quadrotor Agile Flight
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866917382708002816 |
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| author | Zhuang, Ao Yu, Feng Zhang, Tianbao Zhang, Linzuo Zou, Danping |
| author_facet | Zhuang, Ao Yu, Feng Zhang, Tianbao Zhang, Linzuo Zou, Danping |
| contents | We present QuadAgent, a training-free agent system for agile quadrotor flight guided by vision-language inputs. Unlike prior end-to-end or serial agent approaches, QuadAgent decouples high-level reasoning from low-level control using an asynchronous multi-agent architecture: Foreground Workflow Agents handle active tasks and user commands, while Background Agents perform look-ahead reasoning. The system maintains scene memory via the Impression Graph, a lightweight topological map built from sparse keyframes, and ensures safe flight with a vision-based obstacle avoidance network. Simulation results show that QuadAgent outperforms baseline methods in efficiency and responsiveness. Real-world experiments demonstrate that it can interpret complex instructions, reason about its surroundings, and navigate cluttered indoor spaces at speeds up to 5 m/s. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_02786 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | QuadAgent: A Responsive Agent System for Vision-Language Guided Quadrotor Agile Flight Zhuang, Ao Yu, Feng Zhang, Tianbao Zhang, Linzuo Zou, Danping Robotics We present QuadAgent, a training-free agent system for agile quadrotor flight guided by vision-language inputs. Unlike prior end-to-end or serial agent approaches, QuadAgent decouples high-level reasoning from low-level control using an asynchronous multi-agent architecture: Foreground Workflow Agents handle active tasks and user commands, while Background Agents perform look-ahead reasoning. The system maintains scene memory via the Impression Graph, a lightweight topological map built from sparse keyframes, and ensures safe flight with a vision-based obstacle avoidance network. Simulation results show that QuadAgent outperforms baseline methods in efficiency and responsiveness. Real-world experiments demonstrate that it can interpret complex instructions, reason about its surroundings, and navigate cluttered indoor spaces at speeds up to 5 m/s. |
| title | QuadAgent: A Responsive Agent System for Vision-Language Guided Quadrotor Agile Flight |
| topic | Robotics |
| url | https://arxiv.org/abs/2604.02786 |