Humanoid Robot Data Collection

Humanoid robot data collection captures the whole-body behaviors a humanoid needs to learn, teleoperated manipulation, locomotion, balance recovery, and the tail events that determine safety, in homes, labs, and light industrial settings. Operant scopes capture to your platform's morphology and action space, with whole-body synchronization and fall and recovery episodes. The result is humanoid training data matched to how your robot actually moves and where it will be deployed.

Key humanoid modalities

Humanoids combine locomotion, manipulation, and human interaction, so the data spans more modalities than most platforms. We capture synchronized multi-camera RGB-D, proprioception across many joints, IMU, and force/torque, aligned through our multi-sensor synchronization service so whole-body state and action correspond exactly.

Locomotion and manipulation capture

We capture locomotion on varied flooring and terrain alongside reach-and-grasp and bimanual tasks in clutter, with force-relevant metadata. Demonstrations are most often gathered through teleoperation capture, the workhorse method for dexterous, contact-rich humanoid behaviors. Concrete scenarios include humanoid stair ascent and humanoid home navigation.

Recovery and tail events

Humanoids fall, slip, and need to recover. Deliberately capturing these tail events through edge-case data collection is what lets your evaluation reflect real safety risk rather than only successful demonstrations.

Evaluation slices

We design evaluation slices alongside collection, terrain types, clutter levels, recovery scenarios, so you can measure policy behavior under the conditions that matter, not just average-case success.

FAQ

What environments do you capture humanoid data in? Homes, labs, and light industrial settings, scoped to where your humanoid will operate.

Can you capture falls and recoveries safely? Yes, under safety protocols agreed during scoping, combining scripted and opportunistic capture.

Ready to scope a program? This is part of Operant's broader robotics data collection practice.