Enhanced Motion Control of a Self-Driving Vehicle Using Modelica, FMI and ROS

Abstract

This paper presents a new planar wheel model with bore friction, a control strategy to avoid locking conditions of floor vehicles with caster wheels, and the new FMI-Adapter software package, which connects the Functional Mock-up Interface (FMI) standard with the Robot Operating System (ROS). It is demonstrated how this technology enables a convenient model-based control design workflow. The approach is applied to the ActiveShuttle, a self-driving vehicle (SDV) for industrial logistics. After modeling the wheel friction characteristics of the Ac-tiveShuttle, a feed forward controller to avoid high friction torques at the caster wheels in critical operation scenarios is designed and validated by model-in-the-loop simulations. The control function is exported as Functional Mock-up Unit (FMU) for co-simulation. With help of the FMI-Adapter package, the FMU is integrated as ROS node into the service-oriented robot control architecture, enhancing the existing motion controller. The functional-ity and performance is tested and successfully verified on the ActiveShuttle Dev Kit prototype.