Real-world data network
Collect human and robot data across homes, factories, warehouses, retail, and skilled workplaces — including long-tail conditions a lab cannot reproduce.
ROBOT TRAINING DATA FOR EMBODIED AI & VLA
Teach robots
real-world work.
Grasp Labs is a robot training data service for embodied AI, physical AI, and VLA teams — from egocentric human demonstrations and robot teleoperation to multimodal collection, annotation, and training-ready delivery.
Multimodaltime aligned
Real worldat scale
Training-readydelivery
X 0.482Y 0.761WHY GRASP LABS
Not just footage. Experience for robots.
We design robot data collection backward from your model objective, aligning action, vision, force, and physical context. Every trajectory is traceable, validated, and ready for imitation learning, VLA, world-model, or robot-policy pipelines.
Synchronized multimodal capture
Time-align RGB-D, joint states, end-effector poses, force, tactile signals, audio, and language instructions at millisecond precision.
Embodiment-matched collection
Support egocentric capture, portable UMI devices, VR teleoperation, leader-follower rigs, and your target arm, bimanual, or humanoid robot.
Closed-loop data quality
Combine task-success metrics, trajectory checks, sensor validation, failure coverage, and expert review to improve usable data yield.
ROBOTICS DATA SERVICES
Datasets for VLAs, world models, and robot policies.
Egocentric human demonstrations
HUMAN DEMONSTRATION DATAComplete natural task workflows with optional hand pose, gaze, language, and task semantics.
↗Robot teleoperation trajectories
ROBOT TELEOPERATION DATAEmbodiment-aligned actions, joint states, end-effector poses, and multi-view video for imitation learning and policy fine-tuning.
↗Multimodal sensor datasets
PHYSICAL AI DATASynchronized RGB/RGB-D, force, tactile, audio, spatial context, and robot-state data.
↗Evaluation and failure datasets
ROBOT EVALUATION DATASuccesses, failures, recovery actions, and edge cases for policy evaluation and data-engine loops.
↗Robot data annotation and QA
ANNOTATION & QUALITYTrajectory segmentation, event labels, quality scoring, deduplication, privacy processing, and schema conversion.
↗ROBOT DATA COLLECTION PROCESS
From objective to dataset, one production pipeline.
Define
Align on task, embodiment, model interface, data schema, compliance boundaries, and success criteria.
Design
Specify environments, operators, collection hardware, sensors, and quality protocol.
Collect
Deploy trained operators and hardware while monitoring task success and usable trajectory yield.
Deliver
Clean, annotate, validate, version, and deliver directly to your training requirements.
REAL-WORLD ROBOTICS USE CASES
Where robots actually work.
Home manipulation
Industrial manufacturing
Warehouse logistics
Retail service
Dexterous tasks
Long-tail failures
FREQUENTLY ASKED QUESTIONS
Robot training data collection
What types of robot training data do you provide?+
We provide egocentric human demonstrations, robot teleoperation trajectories, RGB-D and multisensor data, success and failure examples, plus data cleaning, annotation, and quality validation.
Can the dataset match our own robot embodiment?+
Yes. We design the action space, sensors, sampling rates, environments, and delivery schema around your arm, bimanual platform, mobile manipulator, or humanoid robot.
Is the data suitable for VLA and embodied AI models?+
Yes. Language, vision, action, robot state, and environment context are time-aligned for VLA models, imitation learning, world models, and robot policy training or evaluation.
How do you validate robotics data quality?+
Each project defines task success criteria, then checks sensor synchronization, trajectory integrity, annotation consistency, failure causes, and long-tail coverage through automated rules and expert review.
Can we begin with a pilot robot dataset?+
Yes. A pilot dataset can validate the task definition, model lift, and data schema before expanding into a continuous or scaled collection program.
START A ROBOT DATA COLLECTION
What should your robot learn next?
Share your target task, robot embodiment, sensors, and model requirements. We will design a first measurable, training-ready dataset.
Contact Grasp Labscontact@grasplabs.com↗