Fueled by the rapid evolution of robotics, the demand for intelligent and lightweight robotic systems continues to grow across industries. However, conventional designs often separate sensing and actuation, resulting in structural complexity and diminished reliability. While integrated sensor-actuator systems offer a promising solution, they face significant challenges in manufacturing and scalability. Liquid crystal elastomer (LCE) are widely utilized in actuators for their thermally responsive deformation and programmability, while Neodymium-Iron-Boron (NdFeB) nanoparticles provide exceptional magnetic properties for sensing. This paper introduces a novel Self-Sensing LCE (SS-LCE) actuator, seamlessly combining LCE and NdFeB to enable simultaneous actuation and self-sensing capabilities. Under thermal stimulation, the actuator executes complex motions while delivering real-time feedback through magnetic field variations. Its programmability and adaptable fabrication process support diverse motion modes, unlocking broad application potential. By enhancing integration, reliability, and flexibility, this self-sensing actuator represents a pivotal advancement in the development of lightweight, intelligent robotic systems with significant research and industrial implications.

Biological machines that use biological cells and soft materials in combination to obtain a sense of the environment driven by bioenergy and generate driving force are called biohybrid actuators. With the development of tissue engineering and organoid technology, researchers have applied biohybrid actuators technology to the research of precision medicine and targeted drug delivery, but the research on feedback and evaluation of biohybrid actuation performance is limited to visual and simulation calculations. Therefore, we hope to develop an intelligent crawling skeleton for sensing function, which can be used to evaluate the actuation ability of muscle actuators, and eventually realize the high-precision control of biohybrid actuators. In this work, an intelligent crawling skeleton based on three-dimensional liquid metal is proposed to detect and feedback the crawling of C2C12 muscle actuators. Three-dimensional muscle tissue was composed of mixing hydrogels and cells, and the functionalization of muscle rings was promoted using static mechanical forces and external electric field stimulation. The composite crawling skeleton is fabricated by inverting mold and soft lithography technology. The skeleton can adapt to large deformations above 90 degrees and is more sensitive to deformations by adjusting materials with different elastic modulus. Inspired by the tendon-bone structure, the intelligent crawling skeleton can obtain the deformation degree of the biohybrid actuator in the crawling process according to the characteristics of the deformation from the muscle tissue, and put forward a good idea for the feedback and closed-loop control of the biohybrid actuators.

The regulation of muscle function is very important for tissue engineering and sports science. This paper presents a simple microfluidic chip platform and its control method to investigate the regulation of muscle function. By employing C2C12 cells as the model system for skeletal muscle research, these cells were inoculated onto the microfluidic chips and induced to differentiate into fully functional muscle tubes. Programmable actuation control enables localized strain gradients within the microfluidic platform, achieving differential mechanical regimes for functional modulation of integrated muscle constructs. The system implements mechanical conditioning to recapitulate exercise-induced myocyte damage and subsequent regenerative processes through controlled deformation protocols. Our radial-strain actuators generate 19.4% maximum principal strain, while axial-strain configurations achieve 8.3% baseline deformation. Dynamic input modulation enables precise strain reduction to 7.4% and 2.2%, respectively establishing differential mechanical regimes for simulating exercise-associated functional impairment (high-strain phase) and recovery processes (low-strain phase). This strain-programmable platform establishes a robust framework for investigating mechanobiological thresholds in functional muscle regeneration.

Tactile information is the research hotspot of wearable flexible sensors due to its importance and complexity. With the innovation of wearable technology and robotics in healthcare, researchers are increasingly integrating wearable flexible sensors on the front end of robots to reproduce the hand tactile manipulation of human tissues. Therefore, it is hoped to develop a thin-film sensor that can be deployed in a small area to assist robots in surgery and data collection of human tissues. Here we use a one-step injection method to fabricate a novel composite sensor based on liquid metal. By laminating multiple PDMS microfluidic layers, the two parameters of pressure and deformation are measured simultaneously in a decoupled manner. The sensor is small and thin, making it easy to integrate into fingers/robot fingers for assistance. The finger/robot finger exerts pressure on the sensor and the sensor deforms with the material to identify the hardness of the material being touched. Separate performance tests of the two sensors show that the strain and pressure functions are decoupled from each other, and their ratios can identify and classify the hardness of different touched materials (glass, PDMS and silicone). This novel composite sensor we proposed can assist robots in manipulating human tissues during medical surgeries. At the same time, its function in tactile information feedback also has broad applications in medical treatment, rehabilitation and services.