The exoskeleton robots to assist load-carrying have received much attention in recent years. However, their load capacity and comfort are still insufficient. In this paper, we have developed a novel parallel actuated lower limb exoskeleton(PALExo), that addresses these problems. The novelty is that each limb of the exoskeleton is a 2-SPU underactuated parallel mechanism. Owing to the innovative series elastic module (SEM) with multi-segment stiffness, PALExo is compliant and comfortable for the wearer. The high load characteristic of the parallel structure increases the exoskeleton load capacity, and it can accommodate wearers of different heights without manual adjustment. A dynamic model of the exoskeleton was established, and in order to increase the robustness of the system, we designed a force control method based on sliding mode control and disturbance observer. Finally, the rationality and load-bearing effect of the exoskeleton were verified through a series of experiments including swing following, squatting and walking with loads.

Soft grippers exhibit impressive grasping performance with great simplicity, compliance, adaptability, and robustness. However, it is a great challenge for them to achieve high-load carrying capacity. Here, we present a soft fabric gripper to achieve high-load carrying capacity. The gripper features a simple structure, easy fabrication, low cost, and high load capacity. As the operating part of the gripper, the cylindrical, unstretchable, and airproof fabric is folded from its axial middle to form two concentric cylindrical layers. The closed cavity between the inner layer and outer layer can be inflated so that to press the inner layer contracting inward to envelop the object achieving grasping. A growth-morphology gripper can be easily achieved by just folding the fabric with more layers, which can perform more friendly interaction with the inner object and the outer environments. The grasping mechanism is studied, and the load capacity is analyzed theoretically and validated experimentally through mechanical load tests. The experiment results validate the theoretical analysis and demonstrate the high-load carrying capacity of the enveloping soft gripper. Profiting from the advantages of the growth morphology of the gripper, a larger-scale prototype is assembled for the application of bore well rescue. The test results demonstrate that the larger-scale prototype can hold 55 kg at 0.09 bar.

Architectured soft structures have unlocked new possibilities for designing continuum manipulators with tailored mechanical performance. This work introduces a bioinspired soft manipulator based on modular wave spring units, leveraging the high elasticity of wave spring structures to enable compliant deformation and axial extensibility of the soft manipulator. To achieve precise control of the soft manipulator, a neural network-based inverse kinematics framework is developed to establish an efficient mapping from desired end poses to tendon actuation lengths. An iterative learning control strategy is further integrated to compensate for material hysteresis, friction, and external disturbances. A prototype is fabricated using flexible 3D-printable material (TPU), and comprehensive experiments are conducted to validate extensible performance, point positioning accuracy, trajectory-tracking accuracy, and compliant interaction capability. The results demonstrate that the proposed wave spring-based soft manipulator achieves a high extension ratio and reliable control precision.

Soft modular grippers play a significant role in multiple fields due to their excellent adaptability and flexibility. This paper proposes a modular soft modular gripper driven by pneumatically actuated multi-chambers. The designed soft modular gripper features three operational modes, with its modular fingers employing independently controlled dual chambers. The distal and proximal dual-chamber structure enhances the fingertip force of the modular fingers. Based on classical laminated plate theory and incorporating the large deformation characteristics of soft materials, a relationship between the bending centerline of the fingers and the driving pressure is established, providing a theoretical foundation for grasping tasks executed by the soft modular gripper. The Denavit-Hartenberg (D-H) parameter method is utilized to develop the coordinate system of the soft modular gripper, thereby defining its operational workspace. Visual sensing technology is introduced, incorporating improvements to the YOLOv8-based object recognition and localization framework, which enhances recognition accuracy for target objects and ensures grasping stability.