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Particle‐jamming soft grippers demonstrate notable shape adaptability and adjustable stiffness, which improve their grasping efficiency. However, integrating tactile sensing into these grippers presents challenges due to the specific properties of the particle jamming mechanism. This study introduces a parallel particle jamming soft gripper equipped with tactile sensing capabilities. The gripper consists of two tactile sensing particle jamming pads (TSPJPs) that are integrated with flexible optoelectronic skins. These skins are made of silicone rubber membranes and are embedded with a 3 × 3 array of stretchable optical waveguide arrays (SOWAs). Testing indicates that incorporating these sensors enhances the gripper's tactile sensing capabilities, with minimal impact on its particle jamming‐based grasping function. A single TSPJP can accurately detect various contact points and estimate the contract forces. The proposed soft gripper can reliably grasp a wide range of objects, varying in shape, hardness, and weight, and it provides detailed tactile feedback on contact locations and the intensity of the grasping through the SOWA sensor. It can precisely distinguish between different grasping postures using a light gradient boosting machine (LightGBM) learning model. Furthermore, it can effectively detect the slippage of grasped objects, facilitating accurate closed‐loop control for secure manipulation.

In wearable robotics, soft actuation principles have been increasingly explored and tested due to their safety and comfort in human–robot interactions. Herein, a braided flat‐tube artificial muscle (BFAM) is presented. BFAMs are fabricated by braiding cotton threads together with an inexpensive lay‐flat tube (LFT) in a specific conform‐to‐LFT weaving method. They generate uniaxial contractions when powered by compressed fluids. The basic structure and working mechanism of the proposed BFAM are explained, and a quasistatic model is also developed. A comparison with other fluidic driven soft actuators is made and tabulated. Based on experimental studies, the proposed BFAM can contract close to 30% and yield force outputs more than 150 times their weight at an air pressure of 0.12 MPa. BFAM can be braided with multiple layers of flat tube without large increase of size. Experimental studies have shown that more layers of flat tube give a larger strain and output force up to four layers, beyond which layer increase does not yield visible improvement in strain and output force. Finally, potential applications of BFAM to arm joint actuations are illustrated to show its easy fitting to wearable robotics.

Pneumatic and tendon‐driven actuators are widely used in soft robotic glove design. Tendon‐driven robotic gloves are generally better in controllability, dexterity, and force output, but they are less comfortable than pneumatic ones. Most soft gloves focus on only one actuation mode where either motor‐driven tendon or pump‐driven pneumatic transmission is used. Herein, a double‐acting soft actuator (DASA) that provides both tendon‐driven flexion and pneumatic extension of fingers by a single motor is presented. This is achieved by a smart pulley and bellow system. The kinematic model of the tendon‐driven flexion and the torque model of the fabric‐based pneumatic extension actuator (FPEA) are developed to analyze the DASA performance. The bending angle of the index finger actuated by the tendon and the FPEA extension torque of a joint are characterized by experimental studies. A cycle test of the DASA is conducted 3000 times, demonstrating its high repeatability. A prototype soft glove (68 g) based on the proposed DASA with a control box (835 g) is fabricated to demonstrate finger flexion and extension assistance. Based on electromyography signals, the performance of the robotic glove is evaluated by a squeezing sponge test.