题目：Continuous-time optimal control for trajectory planning under uncertainty
时间：2025年7月2日（周三），上午9:30—10:30
地点：数学楼2-3会议室
讲座内容：In this talk, we present a continuous-time optimal control framework for the generation of reference trajectories in driving scenarios with uncertainty. A previous work (Zhang et al., 2022a) presented a discrete-time stochastic generator for autonomous vehicles; those results are extended to continuous time to ensure the robustness of the generator in a real-time setting. We show that the stochastic model in continuous time can capture the uncertainty of information by producing better results, limiting the risk of violating the problem's constraints compared to a discrete approach. Dynamic solvers provide faster computation and the continuous-time model is more robust to a wider variety of driving scenarios than the discrete-time model, as it can handle further time horizons, which allows trajectory planning outside the framework of urban driving scenarios.
报告人简介：Abdel Lisser is Full Professor at Université Paris-Saclay since 2001. He led the Graph Theory and Combinatorial Optimisation group at Laboratoire de Recherche en Informatique (LRI) from 2006 to 2014. He moved to Laboratoire des Signaux et Systèmes (L2S) at CentraleSupélec in 2020. He was heading the research group at France Telecom Research Center from 1996 to 2001. He got his Ph.D. in Computer Science at the Université Paris-Dauphine in 1987 and the "Habilitation à Diriger des Recherches" (HDR) thesis at the Université Sorbonne-Paris-Nord in 2000. His main research areas are stochastic optimisation, chance-constrained optimisation and conic optimisation. He works on chance-constrained stochastic games and Markov Decision Processes with chance constraints. Other topics of his research are dynamic neural networks and applications of machine learning in stochastic optimisation and quantum stochastic optimisation. He has already carried out different national and international projects in recent years.
邀请人：刘嘉 副教授
