Key Capabilities
- Industrial Scene Modeling
Build high-fidelity industrial environments from CAD/BIM, facility drawings, asset libraries, and site constraints — optimized for simulation at scale.
- Photoreal Visual Generation
Generate high-quality RGB and synthetic imagery with controllable lighting, textures, and camera optics — supporting robust perception training across real-world variability.
- Physics & Material Properties
Assign physical attributes (mass, friction, restitution, joints, constraints) and material definitions to make interactions realistic — essential for manipulation, contact, and mobility learning.
- Auto-Labeled Ground Truth
Generate consistent large-scale annotations such as segmentation masks, 2D and 3D bounding boxes, instance IDs, depth, keypoints, poses, trajectories, and scene metadata. This also includes invisible data like temperature, pressure, and embedded business logic.
- Industrial Task Goals & Reward Setup
Define goals, success conditions, and reward signals for industrial tasks: tight tolerances, multi-step procedures, safety constraints, partial observability, and domain-specific semantics.
- Export to Training & Simulation Stacks
Package datasets and OpenUSD scenes for downstream training, evaluation, and Sim2Real workflows — including integration paths for NVIDIA Isaac Sim/Omniverse and common robotics toolchains.
개요
DataMesh Robotics generates industrial-grade synthetic training data for embodied AI. Build digital twins, simulate sensors, auto-label ground truth, and export to NVIDIA Isaac Sim/Omniverse and robotics pipelines.
Early Access — DataMesh Robotics is currently available to select enterprise partners. We are working with partners including industrial automation companies to refine simulation-based data generation workflows for real-world robotics applications.
Ready to Accelerate Your Robot Training Pipeline?
Tell us your target robot, tasks, and environment. We'll propose a data generation plan, integration approach, and a demo tailored to your industrial scenario.
Contact us at: robotics@datamesh.com
개요
DataMesh Robotics는 구현 AI를 위한 산업급 합성 훈련 데이터를 생성합니다. 디지털 트윈 구축, 센서 시뮬레이션, 그라운드 트루스 자동 라벨링, NVIDIA Isaac Sim/Omniverse로 내보내기가 가능합니다.
얼리 액세스 — 선별된 엔터프라이즈 파트너에게 제공됩니다.
자주 묻는 질문
What kinds of data can you generate?
We can generate multi-modal datasets such as RGB images, depth, segmentation, instance IDs, 2D/3D bounding boxes, object poses, robot state/trajectories, and scenario metadata. Outputs are configurable to your training goals and target simulator.
Is this only for perception, or also manipulation?
Both. Perception datasets are common, but DataMesh Robotics is built for embodied tasks where physics matters — manipulation, contact-rich interactions, mobility, and inspection actions.
How do you ensure sim-to-real transfer?
We combine industrial-accurate geometry and constraints with physics parameters and structured variation (domain randomization).
Can you integrate with NVIDIA Isaac Sim?
DataMesh Robotics is designed to integrate with OpenUSD-based workflows and can be adapted to support Isaac Sim/Omniverse pipelines depending on your environment and requirements.
Can you work with our proprietary assets?
Yes. We can ingest your assets and help optimize them for simulation while supporting enterprise deployment options to protect IP.
What does a pilot project look like?
A pilot commonly includes one target environment, a small set of tasks, a defined dataset spec, an integration path to your training stack, and a performance validation loop. We also have ready-to-use templates to generate generic training data in certain industries.
Can this be deployed on-premise?
Yes. DataMesh Robotics suites can be used with both cloud and on-premise environments.