collaborators

5 papers

cs.RO2026

Cooperative Informative Sensing for Monitoring Dynamic Indoor Environments via Multi-Agent Reinforcement Learning

Kanghoon Lee, Matthew M. Sato, Jinnyeong Yang +7

Monitoring human activity in indoor environments is important for applications such as facility management, safety assessment, and space utilization analysis. While mobile robot te…

cs.RO2026

Priority-Aware Multi-Robot Coverage Path Planning

Kanghoon Lee, Hyeonjun Kim, Jiachen Li +1

Multi-robot systems are widely used for coverage tasks that require efficient coordination across large environments. In Multi-Robot Coverage Path Planning (MCPP), the objective is…

cs.LG2025

TrajEvo: Trajectory Prediction Heuristics Design via LLM-driven Evolution

Zhikai Zhao, Chuanbo Hua, Federico Berto +4

Trajectory prediction is a critical task in modeling human behavior, especially in safety-critical domains such as social robotics and autonomous vehicle navigation. Traditional he…

cs.AI2025

TrajEvo: Designing Trajectory Prediction Heuristics via LLM-driven Evolution

Zhikai Zhao, Chuanbo Hua, Federico Berto +4

Trajectory prediction is a crucial task in modeling human behavior, especially in fields as social robotics and autonomous vehicle navigation. Traditional heuristics based on handc…

cs.MA2025

Human Implicit Preference-Based Policy Fine-tuning for Multi-Agent Reinforcement Learning in USV Swarm

Hyeonjun Kim, Kanghoon Lee, Junho Park +2

Multi-Agent Reinforcement Learning (MARL) has shown promise in solving complex problems involving cooperation and competition among agents, such as an Unmanned Surface Vehicle (USV…