Guolin Yang

Guolin Yang

Robotics & Autonomous Systems

Hi there! I’m a PhD Researcher in Robotics and AI / Control Systems and Robotics at the University of Manchester, advised by Prof. Guido Herrmann and Prof. Alessandra Parisio. I am also mentored by Dr. Anthony Siming Chen. I expect to complete my PhD in December 2026. Before my PhD, I worked on ADAS software at Lotus Technology and battery-management-system software and validation at NIO.

My research interests include World Models, Model-Based Reinforcement Learning, Motion Planning, Model Predictive Control, and Safe Control. I build predictive autonomous systems that reason about action-dependent future interactions and make real-time decisions in dynamic multi-agent environments.

My recent work includes interaction-aware latent world models for crowd navigation, uncertainty-aware MPPI with CBF/CVaR safety mechanisms, and real-time multi-obstacle safety filtering. Across the reported studies, the best evaluated configuration reached 99.9% navigation success, improved OOD success by 4.8 percentage points, and reduced collision rate from 7.8% to 3.8% with a 9.30 ms safety-filter runtime.


Recent News

Sep 2026Presented Risk-Bounded Predictive Control for Automated Vehicles in Shared-Space Areas at AVEC 2026 in Tsukuba, Japan.
2026A Safety Framework for Uncertainty-Aware Model Predictive Path Integral Control in Shared-Space Navigation accepted to IEEE CDC 2026.
2026PIP-CN: Prediction-Integrated Planning for Crowd Navigation accepted to IEEE/RSJ IROS 2026.
2025Co-authored work on intelligent industrial PV-panel cleaning recommendation published in Applied Energy.
2024A Hierarchical Forecasting Model of Pedestrian Crossing Behaviour for Autonomous Vehicle published in IEEE Access.

Selected Projects

CDC 2026
Safe MPPI trajectory result from the CDC 2026 paper
A Safety Framework for Uncertainty-Aware Model Predictive Path Integral Control in Shared-Space Navigation
Guolin Yang, A. S. Chen, A. Parisio, and G. Herrmann
IEEE Conference on Decision and Control (CDC), 2026
IROS 2026
PIP-CN paper figure comparing prediction-only and planning-informed prediction
PIP-CN: Prediction-Integrated Planning for Crowd Navigation
Guolin Yang, A. S. Chen, A. Parisio, and G. Herrmann
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2026
AVEC 2026
AVEC paper figure
Risk-Bounded Predictive Control for Automated Vehicles in Shared-Space Areas
Guolin Yang, A. S. Chen, A. Parisio, and G. Herrmann
International Symposium on Advanced Vehicle Control (AVEC), 2026
IEEE Access
Hierarchical Forecasting Model figure from the IEEE Access paper
A Hierarchical Forecasting Model of Pedestrian Crossing Behaviour for Autonomous Vehicle
Guolin Yang, E. J. Lopez Pulgarin, and G. Herrmann
IEEE Access, vol. 12, pp. 9025–9037, 2024
SAE China
Autonomous race car lap-time simulation
Time-Optimal Trajectory Planning for Autonomous Race Car
Guolin Yang and T. Chai
China Society of Automotive Engineering Annual Conference, 2020

Research: world models · model-based RL · MPPI/MPC · motion planning · CBF · CVaR · autonomous systems.