Optimal Transport for Applications in Control and Estimation

In recent decades, there has been a rapid development of theory and methods for optimal transport, both within systems and control as well as in other areas such as signal processing, medical imaging, statistics, and machine learning. These advancements have developed optimal transport into an extensive framework with a large set of theoretical and computational tools that can be used to address problems in the areas of systems, control, and estimation. This special issue is organized to introduce optimal transport to a larger audience in the control community and summarize some of the recent progress in the field. The four articles in this issue present both theoretical and computational results, with a focus on the aspects relevant to the field of systems and control.