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.

This thesis presents a model-based design framework for incorporating mechanical intelligence into soft robotics. By integrating smart materials with morphing structures, the framework enhances the adaptability of soft robotic systems. The embedded mechanical intelligence enables the synchronization of multiple smart materials, facilitating self-actuation and customized deformations. This approach advances the development of autonomous and adaptive soft robotic systems.

Soft robotics has significant interest within the industrial applications due to its advantages in flexibility and adaptability. Nevertheless, its potential is challenged by low stiffness and limited deformability, particularly in large-scale application scenarios such as underwater and offshore engineering. The integration of smart materials and morphing structures presents a promising avenue for enhancing the capabilities of soft robotic systems, especially in large deformation and variations in stiffness. In this study, we propose a multiple smart materials based mechanically intelligent structure devised through a model-based design framework. Specifically, the intelligent structure incorporates smart hydrogel and shape memory polymer (SMP). Employing the finite element method (FEM), we simulated the complex interactions among smart material to analyze the performance characteristics of the intelligent structure. The results demonstrate that, utilizing smart hydrogel and shape memory polymer (SMP) can effectively attain large deformation and exhibit variable stiffness due to the shape memory effect. Besides, the shape-morphing structures exhibit customized behaviours including bending, curling, and elongation, all while reducing reliance on external power sources. In conclusion, utilizing multiple smart materials within the model-based design framework offers an efficient approach for developing mechanically intelligent structure capable of complex deformations and variable stiffness, thereby providing support for underwater or offshore engineering applications.

Soft robots developed by smart materials and structures present advantages in adaptability and flexibility for tailored functions in complex environment. However, conventional design methodologies, which heavily depend on experimental procedures, present obstacles to rapid and efficient design iterations. Thus, employing model-based design emerges as an effective approach to support the designs of soft actuators. In this study, the building blocks was proposed employed by model-based design strategy to investigate the novel actuation approach in mechanically intelligent morphing structures. The simulation results demonstrate, utilizing model-based strategy is the efficient way to develop building blocks of different morphing structures. Furthermore, the combined effort of various smart materials enables varied adapabilities and flexibilities. In summary, by integrating different modeling approaches, material models, and contact models, it is feasible to efficiently design the inteligient structures based on the tailored building blocks to specific requirements, thereby providing guidance and support for engineering design.

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.

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.

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.

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 show adaptability and flexibility in grasping irregularly shaped and fragile objects. However, the soft grippers' low loading capacity and limited shaped fitting ability are the main limitations for developing large-scale applications, especially for heavy objects and objects with sharp edges. The particle jamming effect has emerged as an essential actuation method to adjust the stiffness of soft grippers and enhance the lifting force applied to heavy objects. However, in many large and more serious practical grasping applications, soft actuators are expected to show large scales and several-fold stiffness change, which is challenging to achieve the jamming effect in pneumatic or hydraulic systems. In this paper, a novel active particle jamming method is proposed for the design of a particle jamming-based soft gripper. The proposed method uses active hydrogel particles instead of vacuum pressure to achieve the jamming effect. Additionally, the bending behaviors are implemented based on the jamming effect and actuator design. The numerical model is carried out to explore the actuator behaviors, and a brief experiment case is conducted to verify the feasibility. The results indicated that the proposed actuator achieves the functionality of bending actions by swelling the hydrogel particles. The bending performance is enhanced by lowering the trigging temperature and increasing the thickness of the strain-limit layer. Additionally, there is a transition state from bending to curling when increasing the layer of particles.