In this systematic survey, an overview of non-conventional actuators particularly used in soft-robotics is presented. The review is performed by using well-defined performance criteria with a direction to identify the exemplary and potential applications. In addition to this, initial guidelines to compare the performance and applicability of these novel actuators are provided. The meta-analysis is restricted to five main types of actuators: shape memory alloys (SMAs), fluidic elastomer actuators (FEAs), shape morphing polymers (SMPs), dielectric electro-activated polymers (DEAPs), and magnetic/electro-magnetic actuators (E/MAs). In exploring and comparing the capabilities of these actuators, the focus was on eight different aspects: compliance, topology-geometry, scalability-complexity, energy efficiency, operation range, modality, controllability, and technological readiness level (TRL). The overview presented here provides a state-of-the-art summary of the advancements and can help researchers to select the most convenient soft actuators using the comprehensive comparison of the suggested quantitative and qualitative criteria.
Recent trends in bioinspired robotic systems are paving the way for robots to become part of our daily lives. Soft robots, which are widely recognized as the next generation of human-friendly robots, are such a trend. Soft robots are generally more adaptable, more flexible, and safer than their rigid-link counterparts. Research in soft robotics has produced a broad variety of interesting solutions for all sorts of applications ranging from medical engineering and rehabilitation over exploration to industrial handling. This diversity together with a general lack of experience in designing with soft materials has contributed to a design flow that is highly empirical in nature. For soft robots to become mass-producible in the near future, more general design and modeling methods are needed. In this article, we present a method for the design optimization of soft robot modules that effectively combines finite element modeling and gradient-free optimization. To demonstrate the feasibility of the approach, a soft pneumatic actuator is designed and optimized. Performance analysis of the optimization scheme shows the robustness of the solution in the given case.
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