Supporting data for “Data-driven strategies for soft sensing, robot modelling and control”

  Soft/continuum robots are developed with high dexterity, flexibility and adaptability, as inspired by biologies like octopus, elephant trunk and vines. This high compliance
endows them with the advantage of safe interaction with their surroundings or humans, which indicates a wide spectrum of applications. However, unlike conventional rigid-link robots with identified kinematics/dynamics, high flexibility also brings great challenges for their sensing, modelling and control. The infinite degree-of-freedoms (DoFs) and high non-linearity make it hard to find solutions with conventional analytical methods. In such situations, data-driven strategies using learning algorithms are a promising way out to solve these concerns for soft/continuum robots.