collaborators

6 papers

cs.RO2026

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration

Junfeng Chen, YinHang Luo, Xinyi Wang +2

Collaborative capture of dynamic targets is common in nature as an essential strategy for weaker species against the strong. Similar concepts have shown to be useful for numerous r…

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

Melding LLM and temporal logic for reliable human-swarm collaboration in complex scenarios

Junfeng Chen, Yuxiao Zhu, An Zhuo +6

Robot swarms promise scalable assistance in complex and hazardous environments. Task planning lies at the core of human-swarm collaboration, translating the operator's intent into…

cs.RO2026

CoCoPlan: Adaptive Coordination and Communication for Multi-robot Systems in Dynamic and Unknown Environments

Xintong Zhang, Junfeng Chen, Yuxiao Zhu +2

Multi-robot systems can greatly enhance efficiency through coordination and collaboration, yet in practice, full-time communication is rarely available and interactions are constra…

cs.RO2026

SLEI3D: Simultaneous Exploration and Inspection via Heterogeneous Fleets under Limited Communication

Junfeng Chen, Yuxiao Zhu, Xintong Zhang +2

Robotic fleets such as unmanned aerial and ground vehicles have been widely used for routine inspections of static environments, where the areas of interest are known and planned i…

cs.RO2025

DEXTER-LLM: Dynamic and Explainable Coordination of Multi-Robot Systems in Unknown Environments via Large Language Models

Yuxiao Zhu, Junfeng Chen, Xintong Zhang +2

Online coordination of multi-robot systems in open and unknown environments faces significant challenges, particularly when semantic features detected during operation dynamically…