Soft robotics requires structural systems capable of performing complex and programmable deformations to adapt to unstructured or dynamic environments. Shape memory materials (SMMs) offer a promising solution owing to their shape memory effect and stimulus-responsive adaptability. However, actuators relying on a single type of SMM are often constrained by nonlinear actuation behavior and limited stiffness variation, which restrict their ability to achieve coordinated, multifunctional responses. Addressing these challenges, this study introduces a hybrid programmable morphing structure that integrates a shape memory polymer (SMP) and a shape memory alloy (SMA) to realize cooperative actuation and adaptive stiffness variation within a single unit. In the proposed configuration, the SMA springs act as thermally activated actuators that generate deformation. The SMP cylindrical core employs its shape memory effect to realize reversible shape locking and serves as a thermal switch that enables controlled stiffness variation through temperature regulation. A coupled numerical model was established to describe the cooperative behavior between the SMA and SMP components, and the numerical results were validated through experimental testing. The agreement between simulations and experiments confirms the feasibility and repeatability of the proposed design. The structure achieves a maximum bending angle of 55° under dual-SMA actuation and 42° under single-SMA actuation, while maintaining any intermediate shape during thermal cycling. Furthermore, the hybrid system demonstrates a reversible six-fold increase in stiffness and a motion range extending up to three times its original length, representing a significant improvement over conventional single-material soft actuator. Moreover, the proposed hybrid structure offers a flexible strategy for programmable morphing and demonstrates scalable applicability in practical applications, such as adaptive grasping, reconfigurable locomotion, and environmental exploration. In conclusion, this work provides a feasible and generalizable framework for integrating multiple SMM into programmable morphing structures which can be applied into multifunctional soft robotic systems.

The importance of natural environments with rugged deformable terrain from biodiversity, carbon capture, and coastal protection to economic livelihood is significant. However, the current systems available for robots to explore those ecosystems are either large, expensive and intrusive, not application focused or consist of many mechanical parts prone to failure. This study proposes a soft adaptable wheel designed and verified using a novel modelling-based approach suited for such ecosystems. The novel modelling techniques used a 3 part iterative design framework including a kinematic analysis using multi-body dynamics, structural feasibility tests using the finite element method and deformable terrain testing using the discrete element method. The final design operates as a soft fluidic actuator constructed with silicone, able to change its form depending on the task at hand. The proposed model is intended to be a more application-driven design (for rugged deformable terrain), that can more easily be integrated into robotic systems using off-the-shelf components. The simplicity and symmetry of the model can be easily scaled according to the terrain type, load requirements or application of the robotic system, ultimately reducing the time required to be used in environmental applications.

Soft grippers show adaptability and flexibility in grasping irregularly shaped and fragile objects. However, the low loading capacity and less deformation limit the soft gripper for developing large-scale applications. To overcome these limitations, we propose a new concept of a soft actuator with engineered smart particles. The proposed soft actuator is a dual-chamber programmable structure made from an elastic membrane filled with different particles, which can be driven by expanding particle volume or flexible membrane shrinking. Compared to traditional pneumatic or particle-jamming actuators, we use a combination of granular materials and smart materials, which delivers better active performances of large-scale deformation and variable stiffness. The coupled numerical model of the discrete element method and the finite element method is used to demonstrate the concept. The results indicated that the proposed soft gripper achieves the functionality of large deformation by a shrinking membrane or expanding particles. By controlling different design parameters, the actuator bends up to 138 deg, and the stiffness is up to a maximum of nine times of the pneumatic actuator. Additionally, the bending angle and deflections of the gripper actuator first increase and then drop down with increasing particle diameter ratio, actuator length, and elastic modulus of membrane material. Hence, the choice of different parameters must be in a specific range to achieve the required deformation. In conclusion, the soft-grasping gripper actuator can realize large bending deformation and shows potential for developing soft grippers in multi-scale physical scenarios.

Grippers are widely used in many industrial applications, but are limited due to their rigid constructions and no adaptability to varying stiffness. The solution for this would be the use of soft grippers. One way to design soft grippers is to use smart materials, such as hydrogels. Hydrogel soft grippers, unlike their rigid counterparts, take advantage of smart materials' inherent responsiveness and adaptability, removing the need for external power components. To explore the possibilities of using smart hydrogel as the actuator in the soft gripper, we proposed a bilayer structure including temperature sensitive hydrogel and silicone. In order to get insight into the design of these configurations for a gripper, a model consisting of hydrogel was proposed to execute simulations using Finite Element Method (FEM) in Abaqus. The results show, that by modelling different configurations with temperature as input, information can be obtained about mechanical properties such as expansion and bending. Moreover, various forms of deformation can be attained through the utilization of programmable configurations. These configurations can be tailored to achieve deformations in diverse scenarios, including bulk material conveying or underwater applications.

Smart materials are upcoming in many industries due to their unique properties and wide range of applicability. These materials have the potential to transform traditional engineering practices by enabling the development of more efficient, adaptive, and responsive systems. However, smart materials are characterized by nonlinear behaviour and complex constitutive models, posing challenges in modelling and simulation. Therefore, understanding their mechanical properties is crucial for model-based design. This review aims for advancements in numerically implementing various smart materials, especially focusing on their nonlinear deformation behaviours. Different mechanisms and functionalities, classification, constitutive models and applications of smart materials were analyzed. In addition, different numerical approaches for modelling across scales were investigated. This review also explored the strategies and implementations for mechanically intelligent structures using smart materials. In conclusion, the potential model-based design methodology for the multiple smart material-based structures is proposed, which provides guidance for the future development of mechanically intelligent structures in industrial applications.

Soft grippers have shown their ability to grasp fragile and irregularly shaped objects, but they often require external mechanisms for actuation, limiting their use in large-scale situations. Their limited capacity to handle loads and deformations also restricts their customized grasping capabilities. To address these issues, a model-based soft gripper with adaptable stiffness was proposed. The proposed actuator comprises a silicone chamber with separate units containing hydrogel spheres. These spheres exhibit temperature-triggered swelling and shrinking behaviors. In addition, variable stiffness strips embedded in the units are introduced as the stiffness variation method. The validated finite element method model was used as the model-based design approach to describe the hydrogel behaviors and explore the affected factors on the bending performance. The results demonstrate that the actuator can be programmed to respond in a desired way, and the stiffness variation method enhances bending stiffness significantly. Specifically, a direct correlation exists between the bending angle and hydrogel sphere layers, with a maximum of 128° achieved. In addition, incorporating gap configurations into the chamber membrane results in a maximum threefold increase in the bending angle. Besides, the membrane type minimally impacts the bending angle from 21.3° to 24.6°. In addition, the embedded variable stiffness strips substantially increase stiffness, resulting in a 30-fold rise in bending stiffness. In conclusion, the novel soft gripper actuator enables substantial bending and stiffness control through active actuation, showcasing the potential for enhancing soft gripper performance in complex and multiscale grasping scenarios.