A homogeneous pneumatic soft robot may generate complex output motions using a simple input pressure, resulting from its morphological shape that locally deforms the soft material to different degrees by simultaneously tailoring the structural characteristics and orienting the input pressure. To date, design of the morphological shape (inverse problem) has not been fully addressed. This article outlines a geometry–mechanics–optimization integrated approach to automatically shaping a pneumatic soft actuator or robot that achieves the desired deformation behavior. Instead of constraining the robot's geometry within any predefined regular shape, we employ B-splines to allow generation of freeform boundary surfaces, and use nonlinear mechanical modelling and shape derivative based optimization to navigate the high-dimensional design space. Our design framework can readily regulate the surface quality during the morphological evolution, by imposing the geometric constraints in terms of the principal curvatures and the minimal distance between surfaces as penalty functions. The effect of external forces including the gravity and the interaction force at the end-effector is also taken into account to generalize the method for design problems in which the load capability is also pursued. To improve the computational efficiency, suboptimization problems are constructed within a trust region in which the displacement-dependent objective function is approximated by its first-order Taylor polynomial based on the gradient information to avoid frequently performing time-consuming nonlinear finite element analysis. The suboptimization problems are then solved by the quasi-Newton method combined with the backtracking line search strategy. We showcase various applications to validate our design approach, including actuators for basic extension, bending, and twisting motions, and continuous robot arms that can perform desired in-plane and out-of-plane configurations. We also show that our method can address design of multiple chambers for achieving multiple target deformation behaviors, by co-optimizing the morphological shape and air pressures, which is validated by two examples.

Shape morphing is at the core of future research, which shows promise for wide applications ranging from reconfigurable electronics to soft material robots. In this paper, we present a novel buckling-induced mechanism for shape morphing using dielectric elastomer actuators (DEAs), by bonding the planar precursor structure's “feet” with the DEA. With spatially-varying electric fields applied, the inplane deformation of the DEA generates compressive loads to trigger buckling of planar precursors into desired three-dimensional configurations. To enlarge the achievable motion range at the “feet”, we develop a design optimization approach to the electrode arrangement which is concisely described by cosine functions. By numerically optimizing the cosine function coefficients, we obtain the optimal spatially-varying electrodes for various precursors with different patterns of bonding sites. The experimental results demonstrate the remarkable shape-morphing from two dimensions to three dimensional configurations. Our work paves the way to novel actuation mechanisms for shape-morphing structures, with advantages of rapid response and reversible controllability.

Dielectric elastomer actuators (DEAs) are a promising actuation technology in soft robotics owing to their large voltage-induced deformation and rapid response. However, most existing DEA design paradigms are empirical or intuitive, lacking the mathematical modeling and optimization methodology to exploit their actuation capabilities for prescribed motion tasks. In this paper, we present an automatic design methodology to maximize the concerned displacement(s) of DEAs by topology optimization of the applied spatial electric fields (SEFs). Our method is enabled by integrating the freeform SEF profile captured by implicit level sets, and the constitutive model of DEAs incorporating geometric and material nonlinearities and the electromechanical coupling effect, into a gradient-based optimizer. We implement our method for motions of single and multiple degrees of freedom (DOFs) of planar DEAs, and the optimized SEFs have been found to improve the output displacements by more than 75% compared with their intuitive counterparts. We further demonstrate a proof-of-concept application in which our designed two-DOF DEAs can actively drive various host structures to shape-morph from flat sheets to desired three dimensional configurations. Overall, our paper represents the first step toward automatic design of soft DEAs for diverse potential applications in soft machines and robots.

Soft robots have recently evoked extensive attention due to their abilities to work effectively in unstructured environments. As an actuation technology of soft robots, dielectric elastomers exhibit many intriguing attributes such as large strain and high energy density. This work presents a novel dielectric elastomer based soft crawling robot inspired by inchworms. To fill the need of control of the soft robot, a model describing the interaction between the dielectric elastomer actuator and the environment is proposed, which takes inertia, viscoelasticity and friction into consideration. The model can well describe the robot's dynamic performances and the modelling approach used here can be extended to other dielectric elastomer actuators with complicated geometries for control purposes. The obtained model allows us to design a feedforward plus feedback control scheme for the robot to achieve desired motion. Simulation shows fast response and good tracking performances which are further confirmed by the experiments.

Soft actuators play an important role in producing motions in soft robots, and dielectric elastomers have shown great promise because of their considerable voltage-induced deformation. In particular, air-filled dielectric elastomer actuators have been well studied, where the air inside provides prestretches to improve the actuation range. This paper proposes a network of inflated dielectric elastomer actuators, interconnected via a chamber, with the advantages to be highly deformable and continuously controllable. Theoretical analyses show that the networked design is able to largely postpone the occurrence of material failures of the actuators, resulting in a large and continuous actuation range for their control. We further carried out experiments for validation, and the results were largely in line with the theoretical predictions. These findings essentially provide insight into developing networked soft actuators, for achieving large actuation capability.

Soft robots, primarily made out of intrinsically soft materials, have flourished greatly in the past decade due to their advantages such as flexibility and adaptability over rigid-bodied robots. A rich repertoire of soft robots designed from intuitive or biomimetic approaches have been developed to provide new solutions for robots. However, these design approaches are limited by the designers' experience and inspiration, and a systematic design methodology for soft robots is still missing. We tackle this issue by mathematically recasting the design problem under the framework of topology optimization problem. To demonstrate the effectiveness of the proposed methodology, in this paper, we develop a pneumatically actuated soft gripper consisting of three fingers, each finger is able to undergo a free travel bending and deliver a grasping force. Hence, each gripper finger is designed as a continuum compliant mechanism to achieve its maximal bending deformation. The proposed soft gripper with complex shape is directly fabricated through 3D printing technology. Experimental results show that the deflected soft finger is able to achieve a 41° free travel bending and generate 0.68N blocked force upon 0.11MPa actuation pressure. This work represents an important step towards the goal of designing soft robots automatically.