Flexible Tactile Perception Enterprise Secures New Round of Funding, Projecting Tenfold Revenue Growth by 2026 | Exclusive Report 柔性触觉感知企业获新一轮融资，预计2026年公司营收翻10倍｜硬氪首发

TL;DR

• YaoLe Technology secured Pre-A+ funding led by Dinghe Gaoda, with participation from Changshu Auto Trim and Zulong Entertainment, to advance flexible tactile sensing technology for embodied AI applications.
• The company's data glove integrates sensors directly into fabric using a "metal yarn + sandwich matrix" design, eliminating multi-layer issues like slippage and wrinkles that affect data accuracy in traditional gloves.
• There is a significant shortage of high-quality real-world physical interaction data (only ~500k hours globally vs. required 10M+ hours), making tactile data collection critical for training generalizable embodied models.
• YaoLe targets three main customer segments: embodied AI/world model teams needing heterogeneous operation data, industrial/logistics firms seeking ergonomic analysis, and medical rehabilitation providers requiring precise motion tracking.
• The business model positions hardware as an entry point while emphasizing long-term value through standardized data preprocessing services including calibration, cleaning, and temporal alignment.

Why It Matters

This article highlights a critical bottleneck in advancing embodied AI - the severe shortage of high-fidelity tactile interaction data needed to train robots capable of nuanced physical manipulation. As hardware capabilities improve across robotics sectors, the industry faces a paradigm shift where data quality becomes the primary constraint rather than computational power or mechanical design. Companies developing scalable solutions for collecting and processing real-world tactile interactions will play foundational roles in enabling next-generation autonomous systems that can safely interact with unstructured environments.

Technical Details

• Sensor Architecture: Uses pure metal alloy yarns woven directly into fabric matrices rather than printed films or surface-mounted sensors, creating integrated conductive networks within textile structures
• Multi-layer Elimination: Single-piece weaving construction prevents inter-layer displacement during movement, maintaining consistent sensor positioning even when fingers bend or grip objects
• Signal Validation System: Incorporates wrist-mounted wide-angle cameras to cross-reference tactile inputs with visual confirmation of object contact, filtering out false triggers from air gestures or fabric wrinkles
• Modular Design: Separates wearable sensing elements from processing units, allowing individual glove replacement while preserving calibrated measurement parameters across devices
• Material Properties: Employs breathable fabric constructions with internal air chambers that reduce sweat accumulation effects compared to rubberized alternatives commonly used in electronic skin prototypes

Industry Insight

The emergence of specialized tactile data collection platforms represents a strategic inflection point where hardware manufacturers must evolve toward becoming comprehensive service providers offering end-to-end solutions from raw signal capture to model-ready datasets. Successful companies will demonstrate not only superior sensor fidelity but also robust pipelines for synchronizing multimodal inputs (visual, proprioceptive, haptic) while maintaining temporal precision essential for reinforcement learning frameworks. Investors should prioritize firms showing evidence of production scalability at automotive-grade reliability standards, as these capabilities translate most effectively to demanding robotics applications where failure modes carry significant operational consequences.

TL;DR

• 柔性触觉感知企业「尧乐科技」完成Pre-A+轮融资，资金将用于技术研发、产能拓展及场景落地。
• 公司采用“金属纱线+三明治矩阵”传感器技术，实现传感功能与织物的一体化，提升数据采集可靠性。
• 数据手套作为连接人类操作与机器人学习的物理接口，成为填补触觉数据空白的关键路径之一。
• 行业竞争的关键节点在于在保证数据准确性的前提下，实现规模化量产与成本下探。
• 预计2026年，尧乐科技数据手套业务将占到整体营收的一半以上，全年营收预计翻10倍。

为什么值得看

这篇文章揭示了柔性触觉感知技术在具身智能和机器人领域的重要性，特别是如何通过创新的数据手套解决方案解决高质量真实物理交互数据的短缺问题。对于AI从业者而言，了解这一技术路线及其商业化路径有助于把握未来人机交互和数据采集的趋势。

技术解析

• 核心技术：尧乐科技的“金属纱线+三明治矩阵”传感器技术，将纯金属拉丝合金纱线编织成导电网络，嵌入多层织物构成的矩阵中，实现材料与器件的一体化。
• 产品优势：一体织造成型消除了传统手套因层间滑移带来的信号误差，提升了数据采集的可靠性；模块化设计使得手套本体可单独替换、水洗维护，保障了长期采集任务的连续性。
• 应用场景：数据手套主要用于捕捉真实操作中的接触力学信号，适用于具身智能、世界模型与智能座舱等场景，能够以相对标准化的形态实现规模化部署。
• 商业模式：除了交付数据手套外，还提供数据采集、清洗、标定和时间轴对齐等预处理服务，有效降低了客户在模型训练阶段的数据清洗成本。

行业启示

• 数据驱动的未来：随着人形机器人等技术的发展，高质量真实物理交互数据将成为制约行业发展的关键因素，触觉感知技术将迎来快速发展期。
• 技术创新方向：柔性触觉感知技术的创新不仅限于硬件本身，还包括数据处理和算法优化，未来的竞争将集中在如何更高效地获取和处理触觉数据。
• 跨界合作机会：电子皮肤手套厂商需要与具身智能公司、工业企业以及医疗机构等多方合作，共同推动触觉感知技术的应用和发展，形成生态闭环。