Control Design of an Autonomous Moving Platform for Test Tracks

Abstract

In recent years, artificial intelligence, deep learning, and computer vision systems have paved the way for the development of various self-driving vehicles. The risk of testing these vehicles is not negligible, given the high kinetic energy, so testing methods should be chosen carefully. In addition to static objects, the problem of handling dynamic objects during the test cases which are carried out on test tracks as ZalaZONE. Hence dynamic objects are carried by self-driving platforms that do not cause significant material damage to either the test device or the test subject in the event of a loss of control. This paper presents two important aspects of the development of a universal Moving Platform. These are the safety analysis of the onboard architecture to ensure a highly reliable emergency stop and the trajectory tracking methods and the implementation of the associated low-level control loops.