具身智能数据基础设施 Embodied AI Data Infrastructure

真实世界，被捕捉。 Reality, captured. 智能体，被训练。 Intelligence, trained.

把真实世界的动作与交互，转化为可复用、可扩展、可跨模型周期的训练数据。 We turn real-world motion and interaction into reusable, scalable training data that outlives any single model generation.

查看产品Explore Products 联系我们Get in Touch

硬件是入口，
数据是终点。 Hardware is the entry point.
Data is the destination.

01 产品Products

空间级智能基建Full-Body Capture

EDGE Pro

动作捕捉与精细交互场景打造的「空间级」智能基建 Spatial-grade infrastructure for motion capture & fine-grained interaction

0Wearables

30+场景Scenarios

P&PSetup

零穿戴，绝对无感采集Zero wearables, fully passive 无需穿戴任何传感器或粘贴 Marker 点，彻底消除传统动捕的准备成本与操作员疲劳度，大幅提升单日有效采集产能。No sensors or markers. Eliminates setup overhead and operator fatigue, boosting daily capture throughput.

工业级极高解算精度Industrial-grade precision 实现手部（Hand）关节与躯干（WholeBody）关节的同步精细化捕捉。Simultaneous high-fidelity capture of hand joints and whole-body articulation.

抗遮挡与时空同步Occlusion-resilient sync 内置 SMPL-X 全身姿态解算与 Motion Prior 运动先验算法，自动补全被遮挡部位，从容应对极限姿态。SMPL-X solving and Motion Prior algorithms automatically recover occluded body parts under extreme interactions.

全链路数据敏捷兼容Full-pipeline compatibility 一键导出含高精度动作真值的全格式 3D 动捕数据，无缝对接主流 3D 引擎、动画软件及具身智能训练工作流。One-click export of full-format 3D mocap data with ground truth, compatible with major 3D engines and AI workflows.

桌面级捕捉基建Desktop Capture

EDGE Desk

告别数据手套，重塑精细交互。桌面级半身双臂与手物协同捕捉基建 Beyond data gloves — desktop-grade upper-body, dual-arm & hand-object coordinated capture

0Wearables

30+场景Scenarios

P&PSetup

超越手套的「半身+双臂」高精捕捉Beyond-glove upper-body + dual-arm 同步完整解算上半身躯干、双臂运动学数据及手部所有关键节点的毫米级精细捕捉。一套系统满足带臂机器人、半身人形机器人的训练需求。Full upper-body torso, dual-arm kinematics, and mm-level hand joint capture. One system for humanoid robot training.

零穿戴，零贴点，绝对无感采集Zero wearables, zero markers 无需穿戴感应手套或绑缚空间定位器，彻底消除物理设备对手指自然触感的干涉，大幅提升长时间桌面作业的有效采集产能。No gloves or trackers. Preserves natural finger tactility and eliminates fatigue for sustained desktop sessions.

抗遮挡与高密度物理交互Occlusion-resilient interaction 内置高精度姿态解算与 Motion Prior 运动先验算法，有效解决双手交叉、抓取物体时的严重遮挡与时空同步问题。Precision solving and Motion Prior handle severe occlusion from crossed hands and grasping motions.

全链路数据敏捷兼容Full-pipeline compatibility 一键导出含高精「半身+手部」动作真值与物体轨迹的全格式 3D 动捕数据，无缝对接主流 3D 引擎与具身智能训练格式。One-click export of upper-body + hand ground truth with object trajectories for major 3D engines and AI formats.

全场景高效赋能Versatile scenario coverage 完美适配高校双臂机器人/灵巧手实验室、3D 内容手部及上半身动画制作，更是具身智能/灵巧手数据采集的绝佳基础设施。Ideal for university dual-arm labs, 3D animation, and embodied AI / dexterous hand data collection.

02 核心技术Core Technology

Markless Motion Capture

0亿+B+ 神经网络参数Parameters

1mm 捕捉精度Precision

0fps 实时推理Real-time

亿级100M+ 训练数据Training Data

基于十亿参数深度神经网络，融合多目几何重建、SMPL-X 全身解算与 Motion Prior 运动先验补全，稳定输出可验证的具身数据真值。一次真实场景采集，持续导出原始视频、运动数据、场景重建、ego/exo 视角、深度图与分割图——适配 UMI、Ego-centric、Whole-body 等不同训练范式。 Built on a 1B+ deep neural network combining multi-view reconstruction, SMPL-X whole-body solving, and motion prior completion. One real-world capture continuously yields raw video, motion data, scene reconstruction, ego/exo views, depth maps, and segmentation — compatible with UMI, Ego-centric, Whole-body, and beyond.

03 竞争优势Advantage

全维竞争优势分析 Full-Dimension Competitive Edge

为什么 DongThink 是具身智能数据采集的最优解 Why DongThink is the optimal solution for embodied AI data capture

消除「盲区」 Eliminate blind spots

利用RGB 相机的多视角覆盖，当 A 相机遇到遮挡时，B、C 相机依然能捕获特征。相比单目的遮挡和双目的局限，实现了极强的抗遮挡能力。 With RGB cameras, when camera A is occluded, cameras B and C still capture features — far surpassing monocular and binocular limitations.

真·三维物理坐标 True 3D physical coordinates

不同于 MediaPipe 的视觉估算，我们通过三角测量获得绝对物理坐标（XYZ in Meters）。机器人需要知道"向右走"确切是多少米，这是训练具身智能的基础。 Unlike MediaPipe's visual estimation, we obtain absolute physical coordinates (XYZ in meters) via triangulation — the foundation for embodied AI training.

边缘算力压榨 Edge compute optimization

通过 TensorRT 算子级优化与模型蒸馏，在消费级显卡上跑出了工业级的高帧率，无需昂贵的工作站。 TensorRT operator-level optimization and model distillation deliver industrial-grade frame rates on consumer GPUs — no expensive workstations needed.

04 合作伙伴Partners