Wearable strain sensors that detect joint/muscle strain changes become prevalent at human–machine interfaces for full-body motion monitoring. However, most wearable devices cannot offer customizable opportunities to match the sensor characteristics with specific deformation ranges of joints/muscles, resulting in suboptimal performance. Adequate wearable strain sensor design is highly required to achieve user-designated working windows without sacrificing high sensitivity, accompanied with real-time data processing. Herein, wearable Ti₃C₂T_x MXene sensor modules are fabricated with in-sensor machine learning (ML) models, either functioning via wireless streaming or edge computing, for full-body motion classifications and avatar reconstruction. Through topographic design on piezoresistive nanolayers, the wearable strain sensor modules exhibited ultrahigh sensitivities within the working windows that meet all joint deformation ranges. By integrating the wearable sensors with a ML chip, an edge sensor module is fabricated, enabling in-sensor reconstruction of high-precision avatar animations that mimic continuous full-body motions with an average avatar determination error of 3.5 cm, without additional computing devices.

Parameter uncertainties and fluctuated disturbances have brought great difficulties to the smooth and precise control of robot manipulators in some industrial environments. To address these challenges, a robust adaptive sliding mode controller is proposed in this work for accurate control of the robot manipulator. In case of the modeling uncertainties caused by parameters variation during the operational process, the adaptive technique integrated with radial basis function neural networks is utilized. Under such scheme the parameters are automatically adjusted during the tracking process to enhance the system robustness. A new sliding mode disturbance observer is adopted in order to give compensation of the interference and a new variable structure scheme is proposed to effectively suppress the chattering phenomenon. Based on robot assembly and other application verification, the robustness and stability of the proposed approach are demonstrated with superior and smooth tracking performance.

This paper presents a multi-channel SPAS robotic system consisting of two channels of flexible manipulators and an endoscope channel. Each channel of the manipulators is designed based on a parallel mechanism with three sets of super-elastic Ni-Ti rods and universal joints. This design optimizes the structure for flexibility and safety considerations with a simplified structure compared with conventional parallel mechanisms. Flexible shafts are used for torque transmission, allowing the motors to be farther away from the robotic system. The kinematics of the manipulator is derived, and the reachable workspace and dexterity are analyzed. Furthermore, a prototype of the proposed robotic system is presented. The flexibility of the manipulator is verified via stiffness characterization test. The results of the accuracy tests confirmed that the robotic system can implement manipulation arm with acceptable accuracy. The feasibility and effectiveness of applying the robotic system to the practical operation are also demonstrated through experimentations.

This letter presents a miniature manipulator with variable stiffness towards minimally invasive transluminal endoscopic surgery, such as the endoscopic submucosal dissection (ESD). The manipulator comprises hollow modules with holes in the sidewall, compact with a 4 mm diameter, and dexterous with six degrees of freedom (DOFs). Basic operations of grasping and stripping can be achieved via the terminal surgical tools. The flexible tubes and torque coils are adopted to avoid the motion coupling of the joints. The worm gears with an anti-backdrive property are used to transfer power from the motor to the reels. The variable stiffness is achieved by using the spring-sliding block-based driver system, delivering both high payload/accuracy and flexibility. The system is described in detail. The kinematics, workspace and variable stiffness are analyzed. Tests in terms of the grasping force and variable stiffness are conducted. Results show that the grasping force is larger than 3 N, and the manipulator's stiffness can be tuned with high rates of change. The manipulator's performances, such as the dexterity and the coordination of operation under the master-slave configuration, were preliminarily demonstrated through the basic mock-up operations.