8 papers
Onboard Lightweight LLM Reasoning for Human-Aware Safe UAV Navigation
Siwei Cai, Yuwei Wu, Vijay Kumar +1
Aerial robots operating near people must treat a pedestrian, a parked car, and a wall differently, yet conventional perception--planning stacks reduce all of them to occupied geome…
EFLUX: Elastic Multi-Robot Formation Navigation and Adaptation with Agentic LLMs
Jinyuan Zhang, Yuwei Wu, Guangyao Shi +3
Multi-robot teams operating in confined or cluttered environments must adapt both their formation geometry and group topology to navigate through complex obstacles. This adaptation…
PIP-LLM: Integrating PDDL-Integer Programming with LLMs for Coordinating Multi-Robot Teams Using Natural Language
Guangyao Shi, Yuwei Wu, Vijay Kumar +1
Enabling robot teams to execute natural language commands requires translating high-level instructions into feasible, efficient multi-robot plans. While Large Language Models (LLMs…
DroneFL: Federated Learning for Multi-UAV Visual Target Tracking
Xiaofan Yu, Yuwei Wu, Katherine Mao +3
Multi-robot target tracking is a fundamental problem that requires coordinated monitoring of dynamic entities in applications such as precision agriculture, environmental monitorin…
SPAR: Scalable LLM-based PDDL Domain Generation for Aerial Robotics
Songhao Huang, Yuwei Wu, Guangyao Shi +2
We investigate the problem of automatic domain generation for the Planning Domain Definition Language (PDDL) using Large Language Models (LLMs), with a particular focus on unmanned…
Compositional Coordination for Multi-Robot Teams with Large Language Models
Zhehui Huang, Guangyao Shi, Yuwei Wu +2
Multi-robot coordination has traditionally relied on a mission-specific and expert-driven pipeline, where natural language mission descriptions are manually translated by domain ex…
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…
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…