2 citations · 2 across the 8 of their papers we have counts for
8 papers
Toward Wireless Human-Machine Collaboration in the 6G Era
Gaoyang Pang, Wanchun Liu, Chentao Yue +4
The next industrial revolution, Industry 5.0, will be driven by advanced technologies that foster human-machine collaboration (HMC). It will leverage human creativity, judgment, an…
LocDreamer: World Model-Based Learning for Joint Indoor Tracking and Anchor Scheduling
Geng Wang, Zhouyou Gu, Shenghong Li +4
Accurate, resource-efficient localization and tracking enables numerous location-aware services in next-generation wireless networks. However, existing machine learning-based metho…
Hybrid Centralized Distributed Control for Lifelong MAPF over Wireless Connections
Jinghao Cao, Wanchun Liu, Yonghui Li +1
In lifelong multi-agent path finding (MAPF) with many robots, unreliable wireless links and stochastic executions are the norm. Existing approaches typically either rely on central…
Wireless Human-Machine Collaboration in Industry 5.0
Gaoyang Pang, Wanchun Liu, Dusit Niyato +3
Wireless Human-Machine Collaboration (WHMC) represents a critical advancement for Industry 5.0, enabling seamless interaction between humans and machines across geographically dist…
Communication-Control Codesign for Large-Scale Wireless Networked Control Systems
Gaoyang Pang, Wanchun Liu, Dusit Niyato +2
Wireless Networked Control Systems (WNCSs) are essential to Industry 4.0, enabling flexible control in applications, such as drone swarms and autonomous robots. The interdependence…
Floor-Plan-aided Indoor Localization: Zero-Shot Learning Framework, Data Sets, and Prototype
Haiyao Yu, Changyang She, Yunkai Hu +4
Machine learning has been considered a promising approach for indoor localization. Nevertheless, the sample efficiency, scalability, and generalization ability remain open issues o…
Remote UGV Control via Practical Wireless Channels: A Model Predictive Control Approach
inghao Cao, Subhan Khan, Wanchun Liu +2
In addressing wireless networked control systems (WNCS) subject to unexpected packet loss and uncertainties, this paper presents a practical Model Predictive Control (MPC) based co…
A Constrained Deep Reinforcement Learning Optimization for Reliable Network Slicing in a Blockchain-Secured Low-Latency Wireless Network
Xin Hao, Phee Lep Yeoh, Changyang She +3
Network slicing (NS) is a promising technology that supports diverse requirements for next-generation low-latency wireless communication networks. However, the tampering attack is…