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Reference

Humanoid Robotics Glossary

Clear, source-backed definitions of humanoid robotics, embodied AI, robot learning, training data, control, and simulation terms.

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Data & collection
Cross-embodiment data
Cross-embodiment data is robot training data drawn from multiple physical embodiments, such as arms, mobile manipulators, quadrupeds or humanoids with different kinematics, sensors and action spaces. The datasets are aligned or packaged so models can learn jointly from experience produced by different robots, although shared formatting does not make their observations or controls physically equivalent.

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Data & collection
Demonstration
A demonstration is a recorded example of how an intended task or behaviour is performed, usually represented as a time-aligned sequence of observations, states and actions. For humanoid robot learning, demonstrations may come from teleoperation, kinaesthetic guidance, motion capture or autonomous experts and provide targets for imitation.

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Data & collection
Egocentric data
Egocentric data is sensor data recorded from the viewpoint of the person or robot performing an activity, most commonly with a head- or body-mounted camera. It can also include audio, gaze, depth or inertial signals. For humanoid learning, it shows hands, objects and actions from an actor-centred perspective.

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Data & collection
Motion capture
Motion capture is the measurement and reconstruction of a person’s or object’s movement over time, commonly as joint positions, orientations or a fitted body model. Optical markers, cameras and inertial sensors can supply the measurements. Humanoid robotics uses the resulting motion sequences for analysis, imitation and retargeting to a robot body.

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