Maximising Tolerance to Disturbances via Combined Control-Actuation Optimisation for Robust Humanoid Robot Walking

Abstract

Combined optimisation of various robot subsystems as a co-design problem has been shown to identify performant robots. However, classical optimisation methods result in point-optimum solutions that may not ensure robust performance and physical feasibility, i.e., the existence of components with specifications matching the computed optimum value. To address this problem, we present a set-based robust co-design optimisation strategy to maximise disturbance tolerance. Instead of identifying a single point-optimum solution, a so-called solution space evaluates the combination of the largest design space that delivers the necessary performance while being robust to the largest set of disturbances. The utility of the proposed approach is demonstrated via a computational design study of the ergoCub robot. This study focuses on the robots' walking performance, illustrating (1) improvement in task success considering at least 3 times larger magnitudes of disturbances, (2) identifying a set instead of a point-solution in the design-disturbances space, and (3) improving standardisation of the joint actuation design.