Technology

Core sensing, electronics, calibration, communication, and retargeting technologies used in robot training gloves.

Compare flex, magnetic, Hall-effect, and multi-joint tracking architectures.

Combine finger data with hand, wrist, and forearm orientation.

Return robot-side contact events through vibration, tactile, or resistive feedback.

Map human hand kinematics to robot-hand geometry and joint limits.

Establish repeatable zero points, motion ranges, and cross-session consistency.

Capture contact, pressure, and grip-force signals during manipulation demonstrations.

Plan latency, packet timing, synchronization, and multi-glove communication.

Need help selecting the correct architecture?

Start with the robot task, required signals, software environment, and prototype quantity.