Despite the emergence of many soft-bodied robotic systems, model-based feedback control for soft robots has remained an open challenge. This is largely due to the intrinsic difficulties in designing controllers for systems with infinite dimensions. This work extends our previously proposed formulation for the dynamics of a soft robot from two to three dimensions. The formulation connects the soft robot's dynamic behavior to a rigid-bodied robot with parallel elastic actuation. The matching between the two systems is exact under the hypothesis of Piecewise Constant Curvature. Based on this connection, we introduce a control architecture with the aim of achieving accurate curvature and bending control. This controller accounts for the natural softness of the system moving in three dimensions, and for the dynamic forces acting on the system. The controller is validated in a realistic simulation, together with a kinematic inversion algorithm. The paper also introduces a soft robot capable of three-dimensional motion, that we use to experimentally validate our control strategy.

Soft robots’ flexibility and compliance give them the potential to outperform traditional rigid-bodied robots while performing multiple tasks in unexpectedly changing environments and conditions. However, soft robots have not yet revealed their full potential since nature is still far more advanced in several areas, such as locomotion and manipulation. To understand what limits their performance and hinders their transition from laboratory to real-world conditions, future studies should focus on understanding the principles behind the design and operation of soft robots. Such studies should also consider the major challenges with regard to complex materials, accurate modeling, advanced control, and intelligent behaviors. As a starting point for such studies, this review provides a current overview of the field by examining the working mechanisms of advanced actuation and sensing modalities, modeling techniques, control strategies, and learning architectures for soft robots. Next, we summarize how these approaches can be applied to create sophisticated soft robots and examine their application areas. Finally, we provide future perspectives on what key challenges should be tackled first to advance soft robotics to truly add value to our society. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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