Data gloves and motion capture

Training data rewards joint-angle fidelity. Live teleoperation rewards low latency and feedback. Few gloves are best at both.

For fragile, deformable or insertion tasks, force feedback measurably reduces failed demonstrations. For pick-and-place it is a luxury.

Parallel operator stations change the maths. Five mid-tier rigs often out-collect one flagship.

Not every glove ships ROS 2 support today, and a roadmap promise is not a driver. This disqualifies options fast.

Highest capture fidelity in the group and no force feedback at all. EMF tracking is also sensitive to nearby ferrous metal — plan the cell layout around robot arms and steel benches.

The vibration is notification, not resistance. It tells you that you made contact; it does not stop your fingers closing through the object.

Built specifically for tele-robotics and imitation learning, with the thinnest published spec sheet of the group. Buy it for the force feedback; ask us for the datasheet before you spec it on numbers.

A feel device, not a capture device. Five sensors will not produce a 25-DoF anatomical hand. Excellent for VR training, wrong tool if the deliverable is a clean joint-angle dataset.

Adds texture and thermal feedback that nothing else here does — a narrow but real advantage for material-handling research. Not a mocap-grade capture device.

Drives an Inspire hand directly for live demonstration. Treat it as a demo controller, not a dataset-grade capture system, and note it is offered for commercial use only.