Dual-Modal Soft Magnetic Skin With Anti-Magnetic Interference Structure for Tactile Perception

Traditional magnetic tactile sensors often suffer from external magnetic field interference. To address this issue, we first theoretically derived, through mathematical formulations, the fundamental cause of magnetic field interference, providing a solid basis for interference mitigation. Building on this understanding, this work proposes and designs a dual-modal soft magnetic skin with the capabilities to mitigate magnetic field interference. Inspired by the sensory mechanism of human skin, the designed magnetic skin can simultaneously capture dual-modal information, namely magnetic and force tactile information across spatiotemporal domains. A Bi-Convolutional Neural Network–Multilayer Perceptron (Bi-CNN-MLP) is constructed to fuse the dual-modal tactile information. In order to reduce the impact of external magnetic field interference, a novel Dynamic Weighting Coefficient Layer (DWCL) is proposed, which dynamically assigns optimal weights to each modality based on real-time input characteristics. Specifically, by analyzing temporal discrepancies between modalities during pre-contact sensing and quantifying the magnetic field strength of target objects, the DWCL autonomously adjusts fusion ratios to prioritize the modality with higher reliability under varying interference conditions. Furthermore, extensive experimental evaluations from multiple perspectives demonstrate that the proposed electronic skin exhibits robust multi-scale perception capabilities, thereby enabling accurate and stable tactile sensing, while the DWCL achieves substantial improvements in interference resistance compared with traditional fusion strategies.