Soft robots present resilient and adaptable systems characterized by deformable bodies inspired by biological systems. In this paper, we comprehensively review existing design methods for soft robots. One unique feature of our review is that we first formulate criteria, which enables us to derive knowledge gaps and suggest future research directions to close these gaps and go further. Another distinctive feature of our review is that we pivot on the general engineering design process for soft robots. As such, we consider three criteria: (1) the availability of design requirements to start with the design of soft robots, (2) the availability of the so-called concept design or architecture design for soft robots, and (3) the systematic process that leads to the final design of soft robots. The review is conducted systematically, especially when searching for and selecting relevant publications in the literature. The main contribution of this review includes (i) identifying knowledge gaps and (ii) suggesting future research directions to close these gaps and go further.

Hybrid soft leg systems have been studied for advanced gaits of soft robots. However, it is challenging to analyze and control hybrid soft legs due to their nonlinearity. In this study, we adopted dynamic pole motion (DPM) to analyze stability of a nonlinear hybrid soft leg system with dynamic Routh’s stability criterion and to design a proper controller for the nonlinear system with an error-based adaptive controller (E-BAC). A typical hybrid soft leg system was taken as an example, as such a system can easily become unstable and needs a controller to get the system back to a stable state. Specifically, E-BAC was designed to control the unstable hybrid soft leg fast with a minimal overshoot. As a nonlinear controller, the implanted E-BAC in a feedback control system includes two dominant dynamic parameters: the dynamic position feedback $K_p\left(e,t\right)$ and the dynamic velocity feedback $K_v\left(e,t\right)$. These parameters were properly selected, and the feedback was continuously varying as a function of system error $e\left(t\right)$, exhibiting an adaptive control behavior. The simulation shows that this approach for constructing an adaptive controller can yield a very fast response with no overshoot.

This paper explores various fabrication techniques, advances in material development, and strategies to enhance sensor feedback and responsiveness through the function-context-behavior-principle-state-structure (FCBPSS) framework.