Validation of Human-Variability Respecting Optimal Control: A Preparational Study

In order to design a performant and especially well perceived automation to assist the human in physical Human-Machine Interaction, an understanding of the human natural behavior is crucial. Model-based control design is therefore a favorable solution, already being used in various applications. However, most approaches model the human to be deterministic in it’s behavior, not aligning to the state-of-the-art models presented by neuroscience, which more accurately describe the human to be under the influence of noise processes. This paper presents a study that examines 13 participants performing point-to-point movements, followed by the identification of the underlaying cost as well as additive and multiplicative noise process parameters of a human stochastic model. The gained results provide a basis for future automations that explicitly incorporate human variability in their control design.