Minimum time trajectory learning

Abstract

This paper presents an algorithm for finding the minimum time trajectory of an actual dynamic system by using online measurements of the state trajectory. The algorithm is shown to be extremely robust to mismatch between the model and the system. It is a projected gradient method that uses the measured terminal state error of the actual system and gradients based on the theoretical state equation of the system but evaluated along the actual state trajectory. The success of the method is demonstrated on an under actuated double pendulum system called the acrobot.