4 papers
Hierarchical LLMs In-the-Loop Optimization for Real-Time Multi-Robot Target Tracking under Unknown Hazards
Yuwei Wu, Yuezhan Tao, Peihan Li +4
Real-time multi-robot coordination in hazardous and adversarial environments requires fast, reliable adaptation to dynamic threats. While Large Language Models (LLMs) offer strong…
Failure-Aware Multi-Robot Coordination for Resilient and Adaptive Target Tracking
Peihan Li, Jiazhen Liu, Yuwei Wu +1
Multi-robot coordination is crucial for autonomous systems, yet real-world deployments often encounter various failures. These include both temporary and permanent disruptions in s…
Resilient Multi-Robot Target Tracking with Sensing and Communication Danger Zones
Peihan Li, Yuwei Wu, Jiazhen Liu +3
Multi-robot collaboration for target tracking in adversarial environments poses significant challenges, including system failures, dynamic priority shifts, and other unpredictable…
Multi-Robot Target Tracking with Sensing and Communication Danger Zones
Jiazhen Liu, Peihan Li, Yuwei Wu +3
Multi-robot target tracking finds extensive applications in different scenarios, such as environmental surveillance and wildfire management, which require the robustness of the pra…