Path-Following Control of Autonomous Robotic Vehicles with Safety, Liveness, and Performance Guarantees

Autonomous robotic vehicles are increasingly required to operate safely in complex and uncertain environments while meeting stringent performance objectives. This talk addresses motion control from a path-oriented perspective, encompassing trajectory tracking, path following, and time-flexible task execution under nonlinear dynamics, input constraints, and disturbances.
We present a control framework in which safety, liveness, and performance are treated as coupled design objectives. In contrast to classical approaches based on strict temporal constraints, we show how path-parameterized formulations, where the rate of progression along the path is a control decision variable, substantially enlarge the set of feasible and high-performance controllers.
Theoretical developments grounded in Lyapunov methods, input-to-state stability arguments, and optimization-based safety filters are complemented by simulation and experimental studies. Applications include underactuated robotic vehicles and learning-based control architectures for autonomous systems. The talk aims to provide both conceptual insight and practical guidance for designing motion controllers that are safe by construction, live, and performance-oriented.

Short Bio

A. Pedro Aguiar is a Full Professor at the Faculty of Engineering, University of Porto (FEUP), Director of ARISE – Advanced Production and Intelligent Systems Lab, Scientific Coordinator of the Research unit SYSTEC - Research Center for Systems and Technologies, and Head of the Cyber-Physical Control Systems and Robotics Lab. He is also co-director of the Bachelor in Aerospace Engineering, and a member of the Department Executive Committee and the Scientific Committees of the Doctoral Program in Applied Mathematics, and the Master in Data Science and Engineering. He previously held research and teaching positions at IST Lisbon. His research focuses on control systems and robotics, including guidance, navigation, and control of autonomous vehicles, nonlinear control, optimal control, integration of machine learning with feedback control, cyber-physical systems, and quantum control systems. He has led numerous national and international R&D projects and serves as Senior Editor of IEEE Control Systems Letters (L-CSS), Associate Editor of IFAC Automatica, and Editor of IEEE Transactions on Vehicular Technology (TVT).