The aim of this work is to investigate alternative designs for machines intended for biomimetic locomotion in liquid environments. For this, structural compliance instead of discrete assemblies is used to achieve desired mechanism kinematics. We propose two models that describe the dynamics of special compliant mechanisms that can be used to achieve biomimetic locomotion in liquid environments. In addition, we describe the use of analytical solutions for mechanism design. Prototypes that implement the proposed compliant mechanisms are presented and their performance is measured by comparing their kinematic behavior and ultimate locomotion performance with the ones of real fish. This study shows that simpler, more robust mechanisms, as the ones described in this paper, can display comparable performance to existing designs.

Highly ordered Na₂Ti₃O₇@N-GQD nanofiber arrays on carbon textiles (CTs) exhibit high flexibility, excellent cycling stability, and high energy/power densities.

This article presents a versatile soft robotic gripper system whereby its fingers can be reconfigured into different poses such as scoop, pinch, and claw. This allows the gripper to efficiently and safely handle food samples of different shapes, sizes and stiffness such as uncooked tofu and broccoli floret. The 3D-printed fingers were tested to last up to 25 000 cycles without significant changes in the curvature profile and force output profile. A benchmark experiment was conducted to evaluate the performance of the gripper and state-of-the-art gripping solutions. Capability of versatile soft gripper was optimized by integrating vision and tactile sensing facilities. An object recognition system was developed to identify food samples such as potato, broccoli, and sausage. Position and orientation of food samples were identified and pick-and-place pathway was optimized to achieve the best gripping performance. Flexible tactile sensors were integrated into soft fingers and closed-loop force feedback control system was developed. This allowed the gripper to automatically explore and select the most stable grip pose for different food samples. Integration of vision and force feedback system ensure that objects detected by the system would be firmly gripped. The reconfigurable soft robotic gripper system has been demonstrated to perform high-speed pick-and-place tasks (∼3 s per item) with object recognition system, making it a potential solution to food and grocery supply chain needs.

A new generation of soft functional materials and actuator designs has ushered the development of highly advanced soft grippers as adaptive alternatives to traditional rigid end-effectors for grasping and manipulation applications. While being advantageous over their rigid counterparts, soft gripper capabilities such as contact effort are mostly a consequence of the gripper workspace, which in turn is largely constrained by the gripper design. Moreover, soft grippers designed for highly specific grasping tasks such as scooping grains or wide payloads are usually limited in grasping other payload types or in their manipulation versatility. This article describes a reconfigurable workspace soft (RWS) gripper that exploits compliant structures and pneumatic actuators to reconfigure its workspace to suit a wide range of grasping tasks. To achieve desired kinematics, finite element analysis (FEA) studies are conducted to dictate actuator design and materials used. Various grasping modes and their reconfiguration of the gripper workspace are presented and characterized, including the gripper's capability to reliably scoop granular items with radii as small as 1.5 mm, precisely pick items as thin as 300 μm from flat surfaces, as well as grasp large convex, nonconvex, and deformable items as heavy as 1.4 kg. The RWS gripper can modify and increase its grasping workspace volume by 397%, enabling the widest range of grasping capabilities to date achieved by a single soft gripper.