17 papers
Self-Optimizing Control of Continuous Processes Based on Reinforcement Learning
Ziqi Zhuo, Junghui Chen, Lei Xie +1
This paper addresses the Self-Optimizing Control (SOC) problem in industrial continuous processes and proposes a Reinforcement-Learning (RL)-based SOC approach to improve dynamic p…
An Overtaking Trajectory Planning Framework Based on Spatio-temporal Topology and Reachable Set Analysis Ensuring Time Efficiency
Wule Mao, Zhouheng Li, Entao Sun +2
Generating overtaking trajectories in high-speed scenarios is typically addressed through hierarchical planning, which often suffers from local optima due to single initial solutio…
Iterative Learning Control-Informed Reinforcement Learning for Batch Process Control
Runze Lin, Ziqi Zhuo, Junghui Chen +2
A significant limitation of Deep Reinforcement Learning (DRL) is the stochastic uncertainty in actions generated during exploration-exploitation, which poses substantial safety ris…
Vision-Augmented On-Track System Identification for Autonomous Racing via Attention-Based Priors and Iterative Neural Correction
Zhiping Wu, Cheng Hu, Yiqin Wang +2
Operating autonomous vehicles at the absolute limits of handling requires precise, real-time identification of highly non-linear tire dynamics. However, traditional online optimiza…
Robust Spatiotemporal Motion Planning for Multi-Agent Autonomous Racing via Topological Gap Identification and Accelerated MPC
Mingyi Zhang, Cheng Hu, Yiqin Wang +3
High-speed multi-agent autonomous racing demands robust spatiotemporal planning and precise control under strict computational limits. Current methods often oversimplify interactio…
A Rapid Iterative Trajectory Planning Method for Automated Parking through Differential Flatness
Zhouheng Li, Lei Xie, Cheng Hu +1
As autonomous driving continues to advance, automated parking is becoming increasingly essential. However, significant challenges arise when implementing path velocity decompositio…