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20242026
most citedStochastic Tube-based Model Predictive Control for Cyber-Physical Systems under False Data Injection Attacks with Bounded Probability

1 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO2026

ACG-WAM: World-Action Modeling via Action-Conditioned Geometric Latent Prediction

Jiangtao Liu, Zishang Xiang, Yage He +4

World action models jointly learn visual predictionand robot actions, providing a way to use observations ofscene evolution for policy learning. Their video and actionlosses, howev…

cs.RO2026

Optimization-based Safe Trajectory Planning for Autonomous Ground Vehicle in Multi-Floor Scenarios

Zishang Xiang, Runda Zhang, Runqi Chai +3

The development of trajectory planning strategies for autonomous ground vehicles (AGVs) represents a prevailing research interest within the domain of intelligent transportation sy…

eess.SY2025★ 1 cited

Stochastic Tube-based Model Predictive Control for Cyber-Physical Systems under False Data Injection Attacks with Bounded Probability

Yuzhou Xiao, Senchun Chai, Li Dai +2

This paper addresses the challenge of amplitude-unbounded false data injection (FDI) attacks targeting the sensor-to-controller (S-C) channel in cyber-physical systems (CPSs). We i…

cs.DC2025

Robust Set Partitioning Strategy for Malicious Information Detection in Large-Scale Internet of Things

Yuhan Suo, Runqi Chai, Kaiyuan Chen +3

With the rapid development of the Internet of Things (IoT), the risks of data tampering and malicious information injection have intensified, making efficient threat detection in l…

cs.MA2024★ 1 cited

Cost-Aware Distributed Online Learning with Strict Rejection Behavior against Adversarial Agents

Yuhan Suo, Runqi Chai, Senchun Chai +2

Distributed online learning in Internet of Things(IoT)-enabled multi-agent systems(MASs) is highly vulnerable to persistent adversarial interactions, particularly when malicious ag…