activity
20232026
most citedAgent as Cerebrum, Controller as Cerebellum: Implementing an Embodied LMM-based Agent on Drones

6 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

CLOSER-VLN: Closed-Loop Self-Verified Retrieval-Augmented Reasoning for Aerial Vision-Language Navigation

Shaoxuan Li, Xiangyu Dong, Xiaoguang Ma +3

Vision-language navigation (VLN) has recently advanced with large language and multimodal models, enabling agents to follow natural-language instructions in unseen environments wit…

cs.RO2026

PM-Nav: Priori-Map Guided Embodied Navigation in Functional Buildings

Jiang Gao, Xiangyu Dong, Haozhou Li +3

Existing language-driven embodied navigation paradigms face challenges in functional buildings (FBs) with highly similar features, as they lack the ability to effectively utilize p…

cs.CV2026

ViSA-Enhanced Aerial VLN: A Visual-Spatial Reasoning Enhanced Framework for Aerial Vision-Language Navigation

Haoyu Tong, Xiangyu Dong, Xiaoguang Ma +3

Existing aerial Vision-Language Navigation (VLN) methods predominantly adopt a detection-and-planning pipeline, which converts open-vocabulary detections into discrete textual scen…

cs.CV2025

SE-VLN: A Self-Evolving Vision-Language Navigation Framework Based on Multimodal Large Language Models

Xiangyu Dong, Haoran Zhao, Jiang Gao +5

Recent advances in vision-language navigation (VLN) were mainly attributed to emerging large language models (LLMs). These methods exhibited excellent generalization capabilities i…

cs.RO2023★ 6 cited

Agent as Cerebrum, Controller as Cerebellum: Implementing an Embodied LMM-based Agent on Drones

Haoran Zhao, Fengxing Pan, Huqiuyue Ping +1

In this study, we present a novel paradigm for industrial robotic embodied agents, encapsulating an 'agent as cerebrum, controller as cerebellum' architecture. Our approach harness…