ICRA submission 2023 : Holistic view of Inverse Optimal Control


Inverse optimal control (IOC) is a framework used in many fields, especially in robotics and human motion analysis. In this context, many methods of resolution have been proposed in the literature. This article presents the Projected Inverse Optimal Control (PIOC), an approach that puts forward a simple and comprehensive view of IOC methods. Especially, we explain how the presence of uncertainties can be properly addressed in our view. Thus, this article highlights how classical methods can be understood as projections of trajectories in the solution space of the underlying Direct Optimal Control (DOC) problem. This point of view makes it possible to examine projections other than classical, which can be fruitful for researchers in the field. As an example, we propose a projection that allows us to choose the underlying cost functions of an IOC problem in a set. The IOC’s sub-problems are also addressed, such as: modelling observed trajectories, noise measurement and the reliability of solutions obtained by IOC. Our proposal is supported by a simple and canonical example throughout the document.