ROS Implementation of Planning and Robust Control Strategies for Autonomous Vehicles

Abstract

Autonomous vehicles are rapidly emerging as a crucial sector within the automotive industry. Several companies are investing in the development and enhancement of technologies, which presents challenging problems in the context of robotics and control. In particular, this work primarily focuses on the creation of an autonomous vehicle architecture utilizing the robotic operating system (ROS2) framework, accompanied by advanced control algorithms. In order to facilitate the development and implementation of lateral vehicle dynamics controllers, a reduced-size automated car available in GIPSA-Lab is used as an experimental platform. The objective is to design robust controllers capable of achieving optimal tracking and stability. Accordingly, this problem is tackled under different robust control syntheses, considering the H∞ approach: using linear time-invariant (LTI) and linear parameter-varying (LPV) model representations. Several simulation and experimental results are included to demonstrate the efficiency of the controllers.