19 citations · 47 across the 13 of their papers we have counts for
5 papers · 1 filter
Online Planning for Multi-UAV Pursuit-Evasion in Unknown Environments Using Deep Reinforcement Learning
Jiayu Chen, Chao Yu, Guosheng Li +6
Multi-UAV pursuit-evasion, where pursuers aim to capture evaders, poses a key challenge for UAV swarm intelligence. Multi-agent reinforcement learning (MARL) has demonstrated poten…
Active Neural Topological Mapping for Multi-Agent Exploration
Xinyi Yang, Yuxiang Yang, Chao Yu +5
This paper investigates the multi-agent cooperative exploration problem, which requires multiple agents to explore an unseen environment via sensory signals in a limited time. A po…
OmniDrones: An Efficient and Flexible Platform for Reinforcement Learning in Drone Control
Botian Xu, Feng Gao, Chao Yu +3
In this work, we introduce OmniDrones, an efficient and flexible platform tailored for reinforcement learning in drone control, built on Nvidia's Omniverse Isaac Sim. It employs a…
LAGOON: Language-Guided Motion Control
Shusheng Xu, Huaijie Wang, Jiaxuan Gao +3
We aim to control a robot to physically behave in the real world following any high-level language command like "cartwheel" or "kick". Although human motion datasets exist, this ta…
Multi-Agent Vulnerability Discovery for Autonomous Driving with Hazard Arbitration Reward
Weilin Liu, Ye Mu, Chao Yu +6
Discovering hazardous scenarios is crucial in testing and further improving driving policies. However, conducting efficient driving policy testing faces two key challenges. On the…