1 citations · 1 across the 7 of their papers we have counts for
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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…
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…
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…
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…
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…
Accelerated K-Serial Stable Coalition for Dynamic Capture and Resource Defense
Junfeng Chen, Zili Tang, Meng Guo
Coalition is an important mean of multi-robot systems to collaborate on common tasks. An adaptive coalition strategy is essential for the online performance in dynamic and unknown…
Combinatorial-hybrid Optimization for Multi-agent Systems under Collaborative Tasks
Zili Tang, Junfeng Chen, Meng Guo
Multi-agent systems can be extremely efficient when working concurrently and collaboratively, e.g., for transportation, maintenance, search and rescue. Coordination of such teams o…