用磁感应和3D打印柔性结构实现高精度触觉感知，可贴合机器人全身。
Magnet-Based Soft Robotic Skin Using a 3D-Printed Multi-Lattice Structure and CNN-Based Tactile Super-Resolution
- 通过磁性材料与多层晶格结构将接触力转为磁场变化，扩大传感器感知范围。
- 基于CNN的触觉超分辨率模型实时定位接触点，精度达毫米级。
- 结构可定制，适合大尺寸柔性皮肤，适用于人机安全交互场景。
本文提出一种基于磁感应的软体机器人皮肤，集成多层柔性晶格结构、分布式霍尔传感器阵列及触觉超分辨率模型。外部接触力通过嵌入式永磁体转化为磁场变化，晶格结构将这些变化扩散至传感区域，使每个传感器具有大且重叠的感受野，从而在最小盲区下实现大范围感知。晶格参数可调，支持机械柔顺性与传感特性的协同优化。采用隐式建模流程与选择性激光烧结（SLS）3D打印技术，可快速制造贴合复杂曲面的高复杂度结构。基于实验数据训练的卷积神经网络（CNN）能实时估计接触位置与法向力。实验验证了定位精度，并表明系统具备扩展至更大面积的能力，适用于全身体机器人皮肤及安全人机交互。
原文摘要 · Abstract (English)
This paper presents a magnet-based robotic skin that integrates a multilayer soft lattice with distributed Hall-effect sensor arrays and a tactile super-resolution model. External contact forces are converted to magnetic field changes by embedded permanent magnets, and the lattice spreads these changes across the sensing domain. This gives each sensor a large, overlapping receptive field and enables a large sensing area with minimal blind spots. Lattice parameters are tunable, enabling joint adjustment of mechanical compliance and transduction characteristics. An implicit modeling workflow and selective laser sintering (SLS) 3D printing support rapid fabrication of conformal, high-complexity structures. A convolutional neural network trained on experimental measurements estimates contact location and normal force in real time. Experiments validate localization accuracy and indicate scalability to larger surfaces, suggesting applicability to whole-body robotic skin and safe human-robot interaction.
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