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DOBOT ATOM D

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About DOBOT ATOM D

DOBOT ATOM D is a data-collection platform for robot-system development and training.


Manufacturer

🏢

DOBOT

CN

Key Specifications

Weight
20 kg
Status
ACTIVE
Category
Humanoid
ATOM D: data collection / Arms
2
ATOM D: data collection / Head DoF
2 DoF
ATOM D: data collection / Image data
Colour binocular video
ATOM D: data collection / DoF per arm
7 DoF (Per arm)
ATOM D: data collection / Depth camera
Intel RealSense D455
ATOM D: data collection / Vision system
Full HD binocular
ATOM D: data collection / Data connection
Ethernet
ATOM D: data collection / Viewing devices
VR / MR
ATOM D: data collection / Video frame rate
60 fps
ATOM D: data collection / External computer
Ethernet data transfer
ATOM D: data collection / Maximum depth range
≤6 m
ATOM D: data collection / End-effector options
Hands / grippers / cameras (According to selected configuration)

Verified ecosystem

Software and resources

Official links and community projects are shown separately. Every published relationship has reviewable evidence.

0
verified official resources
0
verified compatible projects
0
public maintainers
No activity yet
latest verified ecosystem activity

Projects are ordered only within this robot ecosystem using verified compatibility, GitHub freshness and activity, and accepted community reports. This is not a global RobotSpace score.

Official resources

No first-party resource has been independently verified yet. Unverified catalog links are not shown as official.

Official software

No official software project has been verified yet.

Community projects

No verified community project has been linked yet.

Developers and contributors

No public maintainer profile is linked yet.

Verified activity

No verified project activity is available.

This ecosystem is still empty

The robot page remains useful for specifications while official resources and compatible projects are being verified.

Imported from the Unibot owner catalog · Not independently verified · Imported 2026-11-11 · Unibot source · Methodology