Abstract: In intricate aquatic environments, enhancing the sensory performance of underwater actuators to ensure successful task execution is a significant challenge. To address this, a biomimetic tactile multimodal sensing approach is introduced in this study, based on TriboElectric NanoGenerator (TENG) and Micro-ThermoElectric Generator (MTEG). This method enables actuators to identify the material properties of underwater target objects and to sense grasping states, such as pressure and relative sliding. In this study, a multi-dimensional underwater bionic tactile perception theoretical model is established, and a bionic sensing prototype with a sandwich-type structure is designed. To verify the performance of pressure feedback and material perception, pertinent experiments are conducted. The experimental results reveal that within a pressure measurement range of 0–16 N, the detection error of the sensor is 1.81%, and the maximum pressure response accuracy achieves 2.672 V/N. The sensing response time of the sensor is 0.981 s. The recovery time of the sensor is 0.97 s. Furthermore, the exceptional fatigue resistance of the sensor is also demonstrated. Based on the frequency of the output voltage from the prototype, the sliding state of the target object relative to the actuator can be sensed. In terms of material identification, the temperature response accuracy of the sensor is 0.072 V/°C. With the assistance of machine learning methods, six characteristic materials are identified by the sensor under 7 N pressure, with a recognition accuracy of 92.4%. In complex marine environments, this method has great application potential in the field of underwater tactile perception.

Key words: Bionic multi-dimensional sensing')">Bionic multi-dimensional sensing, Triboelectric nanogenerator, Micro-thermoelectric generator, Identification of characteristic material, Grasping pressure perception