Precise perception of surface tackiness enabled by a soft single-sensing-element tactile sensor

Tactile sensors are essential for robots to interact with complex environment, but the precise perception of surface tackiness remains a critical challenge for robotic interactive intelligence. Quantitative adhesion analysis requires measuring both pressure and pulling forces at the exact same location. However, existing sensors struggle with signal crosstalk and baseline instability, failing to achieve this intrinsically decoupled measurement. Here, we report a surface-soft, magneto-mechanical coupling tactile sensor that achieves intrinsic signal decoupling within a single sensing element. By leveraging a skin-like bidirectional deformation design, inward pressure and outward pulling force generate baseline-separated magnetic signatures. This eliminates the need for complex post-processing and enables continuous, high-stability monitoring of the full adhesion cycle-from initial contact to final pull-off. The sensor exhibits only 0.25% force drift over 10 h and remains below 0.30% after hammer strikes and maintains 99.52% signal coincidence across repeated press-pull cycles. Such exceptional performance metrics grant the sensor a level of tackiness differentiation that rivals standard adhesion testing. When integrated with a neural network, the sensor yields 99.78% tackiness identification accuracy under diverse contact conditions, exceeding human precision (85.71%). This work pushes the boundaries of existing tactile sensing and lays a solid foundation for advanced robotic manipulation of tacky and lightweight objects.