A new range of nanomaterial strain sensors holds the promise of improved safety and precision when used with industrial robotic arms. The sensors, developed by National University of Singapore (NUS) researchers, are 10 times more sensitive than existing technology designed to measure minute movements.
The novel strain sensors use MXenes — flexible, stretchable and electrically conductive nanomaterials. They are ultra-thin, battery-free and can transmit wirelessly, making them useful in a number of applications.
Assistant Professor Chen Po-Yen explained that the characteristics of current sensing materials have limited the performance of conventional strain sensors, resulting in fewer options for users to customize them for specific applications. “In this work, we have developed a facile strategy to control the surface textures of MXenes, and this enabled us to control the sensing performance of strain sensors for various soft 
Lightweight strain sensors can be incorporated into rehabilitation gloves to improve their sensitivity and performance. Source: NUSexoskeletons. The sensor design principles developed in this work will significantly enhance the performance of electronic skins and soft robots," Chen said.
Precision manufacturing, such as fabrication of microchips, is one area where these strain sensors would be especially useful. They can be coated on a robotic arm and measure subtle movements as they are stretched. Placement of these sensors along the arm’s joints allows the system to understand exactly how much the robotic arm is moving and its current position relative to the resting state. The new strain sensors provide automated feedback on precise movements, eliminating the need for external cameras used to monitor conventional automated robotic arms in precision manufacturing and offer an error margin below one degree.
Sensor accuracy increases with a high signal-to-noise ratio because it can differentiate between subtle vibrations and minute movements. The breakthrough production process allows for the customization of sensors to any working window (how much the sensor can stretch and still maintain its sensing qualities) between 0% and 900% as well as high signal-to-noise ratio. For comparison, standard sensors can achieve a range of up to 100%. The NUS researchers combine multiple sensors with different working windows to create a single ultra-sensitive sensor and has engineered a working prototype of the application of soft exoskeletons in a soft robotic rehabilitative glove.
"These advanced flexible sensors give our soft wearable robots an important capability in sensing patient's motor performance, particularly in terms of their range of motion. This will ultimately enable the soft robot to better understand the patient's ability and provide the necessary assistance to their hand movements," said associate professor Raye Yeow, who heads a soft robotics lab in NUS Department of Biomedical Engineering, and leads the Soft and Hybrid Robotics program under the National Robotics R&D Program Office.
