A multi-modal sensing method based on triboelectric nanogenerator and micro thermoelectric generator for reliable grasping of underwater robotic arm

The deep-sea region, inaccessible to human beings, is now accessible through the utilization of underwater robotic arms. Due to the complexity and unpredictability of the underwater environment, the robotic arms operating in such conditions must possess higher grasping capabilities. In this study, a multi-modal sensing method based on triboelectric nanogenerator (TENG) and micro thermoelectric generator (MTEG) for reliable grasping of underwater robotic arm is proposed. A theoretical model for multi-modal cooperative sensing is established. A fluid state sensor prototype based on MTEG and a grasping state sensor prototype based on TENG are fabricated. An experiment system for verifying the performance of fluid state and grasping state sensing is established. And the experiment research is conducted. The experiment outcomes demonstrate that the output voltage of the fluid state sensing unit (FS-SU) correlates distinctly with water flow velocity and direction. Concurrently, a posture feedback control method based on FS-SU enhances the operation precision of the robotic arm. The sum of the output voltages of the grasping state sensing unit (GS-SU) demonstrates a positive correlation with the applied pressure. Within the pressure range of 0–4 N, the correlation coefficient is 2.641, and within the range of 4–13 N, the correlation coefficient is 1.089. The difference in output voltages of the GS-SU effectively reflects the relative sliding state between the robotic claw and the object. This method can effectively enhance the operational accuracy and stability of underwater robotic arms. It provides a solution for the automation and intellectualization of underwater tasks.