可编程调控每个微单元的软硬变化，让机器人像跳舞一样灵活变形。
VSL-Skin: Individually Addressable Phase-Change Voxel Skin for Variable-Stiffness and Virtual Joints Bridging Soft and Rigid Robots
- 通过独立控制每个微单元的相变状态，实现厘米级精度的软硬分布调节。
- 在轴向、剪切等方向上实现15至1200 N/mm的近两倍刚度调节，压缩30%仍保持结构完整。
- 支持自修复与可预测失效设计，适合需要灵活重构的机器人系统研究者。
软体机器人具有柔顺性但难以承载负载或保持形状，而刚性机器人虽强度高却缺乏适应性。现有可变刚度系统通常作用于整体段落或区域，难以精确控制刚度分布与虚拟关节位置。本文提出首个可个体寻址的相变体素皮肤（VSL-Skin），实现厘米级精度的形态学控制。该系统可在轴向（15-1200 N/mm）、剪切（45-850 N/mm）、弯曲（8×10²-3×10⁴ N/deg）和扭转模式下实现近两个数量级的刚度调节；首次实现相变系统中30%的轴向压缩并维持结构完整性；并通过热循环实现组件级自主修复，消除疲劳累积，支持可编程牺牲关节用于可控失效管理。选择性激活体素可生成六种典型虚拟关节类型，兼具可编程柔性与非激活区域的结构完整性。平台融合闭式设计模型与有限元分析，实现刚度模式与关节位置的预测性合成。实验验证表明，系统具备30%轴向收缩能力，热切换周期为75秒，裁剪后仍保持寻址能力。行列架构支持跨平台部署，无需专用基础设施。本框架将形态智能作为可工程化的系统属性，推动自主可重构机器人的发展。
原文摘要 · Abstract (English)
Soft robots are compliant but often cannot support loads or hold their shape, while rigid robots provide structural strength but are less adaptable. Existing variable-stiffness systems usually operate at the scale of whole segments or patches, which limits precise control over stiffness distribution and virtual joint placement. This paper presents the Variable Stiffness Lattice Skin (VSL-Skin), the first system to enable individually addressable voxel-level morphological control with centimeter-scale precision. The system provides three main capabilities: nearly two orders of magnitude stiffness modulation across axial (15-1200 N/mm), shear (45-850 N/mm), bending (8*10^2 - 3*10^4 N/deg), and torsional modes with centimeter-scale spatial control; the first demonstrated 30% axial compression in phase-change systems while maintaining structural integrity; and autonomous component-level self-repair through thermal cycling, which eliminates fatigue accumulation and enables programmable sacrificial joints for predictable failure management. Selective voxel activation creates six canonical virtual joint types with programmable compliance while preserving structural integrity in non-activated regions. The platform incorporates closed-form design models and finite element analysis for predictive synthesis of stiffness patterns and joint placement. Experimental validation demonstrates 30% axial contraction, thermal switching in 75-second cycles, and cut-to-fit integration that preserves addressability after trimming. The row-column architecture enables platform-agnostic deployment across diverse robotic systems without specialized infrastructure. This framework establishes morphological intelligence as an engineerable system property and advances autonomous reconfigurable robotics.
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