XDOF Alternative for Robotics Data Collection

Looking for robotics training data? Encord is the top XDOF alternative for egocentric, embodied, and sensor data collection.

Hero image
forterra_logo
Weave robotics
archetype
agility_robotics_logo
Woven by Toyota
zipline
Toyota research institute
standard ai
hitachi_energy_logo

Your partner for robotics data

Evaluating alternatives to XDOF data collection? Partnering with Encord gives you access to vetted domain experts specific to your embodiment, dedicated lab facilities, and bespoke protocol design for your robots.

RGB-D Teleoperation data of hands on table

Egocentric data

First-person video & sensor data of humans performing tasks in household, industrial, and commercial environments. Collected using head & wrist cameras at 1080p/30FPS.

Humanoid robot stacks dishwasher

Embodiment-specific data

Operators run daily tasks custom to your robot - minimising cross-embodiment skill transfer - to produce the highest-fidelity training signal for your deployment config.

Teleoperation putting away cereal in kitchen

Teleoperation data

Leader/follower teleoperation machines operated by trained humans perform high-dexterity tasks - ideal for manipulation, grasping, and fine motor skill training.

UMI grippers grabbing plastic animals on table

UMI data

Handheld gripper systems capture robot-analogous manipulation data without a full robot - including standard UMI, multi-finger variants, and client-provided grippers.

“A big reason why we decided to partner with Encord was because of the quality bar we saw in doing POCs with a dozen companies.”

Devi Parikh

Devi Parikh

Co-Founder & Co-CEO of Yutori

End-to-end collection coverage

Built around your training loop

Tick iconTick icon

Bespoke protocol design

Data collectionData collection

In-field operator network

AnnotationAnnotation

Bay Area lab facilities

SDK integrationSDK integration

Zero ingestion overhead

Decision treeDecision tree

Standardized equipment

Close the deployment loop

Robotics teleoperation instructions

Design your collection protocol

Ask our dedicated robotics team about your specific collection requirements.

Book a call

Frequently asked questions

  • Four types: embodiment-specific data, teleoperation data, egocentric data, and UMI handheld gripper data, including multi-finger variants and customer-provided hardware.

  • Collection starts at Encord facilities, not in the field. Tasks, hardware setup, and quality criteria are defined with your team, then piloted in a controlled lab environment before scaling. Iteration happens before operators deploy, so cost and time aren't spent recollecting data that doesn't match your training objective.

  • Collection is designed backwards from training - every episode is classified, synchronised, and ready-to-use by default, and your data flows directly into the Encord platform.

  • Diversity is built into protocol design, environments, lighting, operators, embodiments, and task variations are specified upfront, not left to chance during collection. Encord operates across multiple geographies and embodiment configurations, with hardware vendor partnerships (including teleoperation arm and biometric sensor providers) to close specific gaps in your training set.

  • Encord already works with more than 300 AI teams building AI models for real-world environments. With Encord, you get access to an expert network of in-field operators, dedicated facilities in the Bay Area, and zero ingestion overhead through the Encord platform.

Abstract dither gradient

Get the data right

The leading frontier AI teams use Encord. Join them.