Shape memory alloys (SMAs) are popular as actuators for soft bioinspired robots because they are naturally compliant, have high work density, and can be operated using miniaturized on‐board electronics for power and control. However, SMA actuators typically exhibit limited bandwidth due to the long duration of time required for the alloy to cool down and return to its natural shape and compliance following electrical actuation. This challenge is addressed by constructing SMA‐based actuators out of thermally conductive elastomers and examining the influence of electrical current and actuation frequency on blocking force, bending amplitude, and operating temperature. The actuator is composed of a U‐shape SMA wire that is sandwiched between layers of stretched and unstretched thermal elastomer. Based on the studies, the ability is demonstrated to create a highly dynamic soft actuator that weighs 3.7 g, generates a force of ≈0.2 N, bends with curvature change of ≈60 m−1 in 0.15 s, and can be activated with a frequency above 0.3 Hz with a pair of miniature 3.7 V lithium–polymer batteries. Together, these properties allow the actuator to be used as an “artificial muscle” for a variety of tethered and untethered soft robotic systems capable of fast dynamic locomotion.

By using compliant lightweight actuators with shape memory alloy, we created untethered soft robots that are capable of dynamic locomotion at biologically relevant speeds.

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Recently, a large number of lightweight flexible structures are successfully used in the field of aerospace industry, intelligent robot and 3D printing. Because of the increasing flexibility of elastic components, some large scale mechanical systems will perform typical rigid-flexible coupled dynamic characteristic. Previous studies have indicated that the traditional modeling methods of the flexible multibody system based on the assumptions of small rotations and small deformation, such as the floating frame of reference method, can not lead to correct results for the dynamic response of those large deformation structures. Under the framework of Isogeometric analysis, the basis functions of the NURBS are employed to discretize the displacement field of elastic components with large deformation. Based on the large deformation theory of the continuum mechanics, the geometrical nonlinearity of planar structures undergoing the overall motion and large deformation is accurately taken into account. In order to improve the computational efficiency, some efficient formulations to calculate the elastic force and the tangent stiffness matrix are proposed via the invariant matrix method. Furthermore, based on the finite element tearing and interconnecting (FETI) method, an efficient parallel algorithm is presented to deal with the dynamic equations of motion for flexible multibody systems. First, the governing partial differential equations of multibody systems are transformed into a set of nonlinear algebraic equations after spatial and time discretization. Then, the preconditioned conjugate gradient method is exploited to solve the linearization equation in parallel. Compared with the existing parallel direct methods for flexible multibody systems, the proposed method can improve the computational efficiency significantly. Finally, several numerical examples are given to validate the effectiveness of the proposed parallel algorithm, including the complexity, the speed-up ratio and the scalability. flexible multibody systems with large deformation, domain decomposition, parallel computation, finite element tearing and interconnecting (FETI) method

We present a quantum annealing-based solution method for topology optimization (TO).In particular, we consider TO in a more general setting, i.e., applied to structures of continuum domains where designs are represented as distributed functions, referred to as continuum TO problems. According to the problem's properties and structure, we formulate appropriate sub-problems that can be solved on an annealing-based quantum computer. The methodology established can effectively tackle continuum TO problems formulated as mixed-integer nonlinear programs. To maintain the resulting sub-problems small enough to be solved on quantum computers currently accessible with small numbers of qubits and limited connectivity, we further develop a splitting approach that splits the problem into two parts: the first part can be efficiently solved on classical computers, and the second part with a reduced number of variables is solved on a quantum computer. By such, a practical continuum TO problem of varying scales can be handled on the D-Wave quantum annealer. More specifically, we concern the minimum compliance, a canonical TO problem that seeks an optimal distribution of materials to minimize the compliance with desired material usage. The superior performance of the developed methodology is assessed and compared with the stateof-the-art heuristic classical methods, in terms of both solution quality and computational efficiency. The present work hence provides a promising new avenue of applying quantum computing to practical designs of topology for various applications.