Towards the Best Robot for the Job: Optimising Actuation Design through Multi-Task Co-Design and Component Selection
Wesley Roozing, Jonathan Cornee Schaaij, Alessandro Forino
Abstract
We propose a multi-task co-design approach to design a robot's actuation (motor sizes and gear ratios) based on trajectory optimisation. Leveraging an actuation model fit on data of series of components, we find the optimal set of design parameters for all joints over a set of representative tasks for the given robot. Critically, we close the loop towards component selection, given a finite set of available components. This enables more practical use of co-design tools. Our results show that the method is effective, and critically, show that it is possible to find a robot design that is capable of performing an entire set of tasks at an efficiency that is comparable to a robot co-designed for each specific task. Finally, we perform an extensive analysis of hyperparameter effects, and select discrete actuation components from catalogues and compare to co-design results.