25 May 2023
Soft robotics involve systems composed primarily of materials with mechanical properties comparable to those of living tissues, for example, easily deformable matter such as elastomers and gels. For that reason, soft robotics control is an interdisciplinary field, spanning material science, biology, continuum mechanics, and, of course, robotics. Navigating this landscape can be daunting: each discipline comes with unique literature, hypotheses, notations, and terminology, adding to the complexity. Furthermore, the field requires consensus on dynamic equations that model soft robots, an active research topic itself.
Soft robots are subjected to an elastic potential field and stabilising dissipation forces while being inherently underactuated and highly nonlinear systems. The task of the control engineer involves harnessing these properties to generate precise motions with limited actuation sources, execute controlled interactions, or store energy during dynamic movements.
In their paper published in the IEEE Control Systems Magazine, EMERGE partner Cosimo Della Santina, from the Delft University of Technology (NL), and collaborators aim to streamline the domain of soft robotics for control theory researchers.
The group introduces soft robotics control via a model-based lens, starting with a unified formulation of soft robot dynamics. It then addresses the challenges of shape control, tracking, underactuation, environmental interactions, actuator dynamics, task space control, and data incorporation in a model-based context. The article also reviews pertinent literature and presents novel results leveraging techniques for rigid robot control.
Source: C. Della Santina, C. Duriez and D. Rus, "Model-Based Control of Soft Robots: A Survey of the State of the Art and Open Challenges," in IEEE Control Systems Magazine, vol. 43, no. 3, pp. 30-65, June 2023, DOI: 10.1109/MCS.2023.3253419.
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