Octopus-inspired multichannel tactile sensor for enhanced underwater material identification

The sustainable development of the ocean requires sensors capable of detecting objects in underwater or high humidity conditions. However, traditional sensors struggle in complex underwater environments due to signal attenuation, biofouling, and flow interference, which seriously affect their performance and reliability. Inspired by the tactile system of octopus suckers, we developed a tactile sensor that mimics the structure of octopus tentacle suckers, ingeniously harnessing triboelectric tactile receptors (TTRs) to emulate the mechanism of cephalopod-specific chemoreceptors (CRs), aiming to address the challenging problem of underwater object recognition. Additionally, the superhydrophobic treatment enhances the microstructure of the sensor surface, effectively mitigating environmental interference and improving underwater performance, leading to a 67 % increase in voltage output, a sensitivity of 0.195 V kPa-1, and a remarkable response time of 85 ms. Most importantly, we have constructed an underwater material identification system (UMIS) to achieve 98 % accuracy by integrating machine learning, which enables precise identification and quantitative sensing of underwater objects, and offering novel insights and directions for the intelligence and autonomy of underwater robots.