Robotics integration
Dexterous hand teleoperation integration
Map human hand motion to robotic hands with a practical evaluation of degrees of freedom, kinematics, control protocols, latency, and data requirements.
From motion capture to robot response
We help teams evaluate the complete path from a glove or exoskeleton signal to robotic hand commands, including motion mapping, controller interfaces, safety limits, and demonstration replay.
Integration scope
- Degrees-of-freedom and kinematic mapping
- Human-to-robot motion scaling and calibration
- SDK, ROS2, and controller interface review
- Latency, synchronization, and robot-state feedback
- Demo deployment and data capture planning
Who it is for
Dexterous robotics startups, university labs, research institutes, robot hand manufacturers, and embodied AI teams.
How an integration evaluation works
The evaluation starts with the robot hand model, joint configuration, controller interface, operating system, and intended task. Human hand output is then compared with the robot's available degrees of freedom and mechanical limits. This identifies where direct mapping is possible and where scaling, coupling, inverse kinematics, filtering, or task-specific constraints are required.
Control and safety considerations
Live teleoperation should define command limits, update frequency, disconnect behavior, emergency stopping, and recovery after tracking loss. These controls are especially important when the operator's natural range of motion differs from the robot's joint limits or when multiple fingers are mechanically coupled.
Demonstration and data handoff
A complete workflow can include operator pose, mapped commands, robot joint state, camera data, timestamps, and task labels. Recording both the input and the robot response helps teams validate latency, review unsuccessful trials, and prepare demonstrations for imitation learning or experiment replay.
What should a team provide before evaluation?
Provide controller or API documentation, joint limits, degrees of freedom, supported command modes, operating system, target update rate, and one or two representative tasks. This is normally enough to identify the first integration path and the main technical risks.
Recommended input device: Review the VetraGlove Pro teleoperation glove for EMF-based hand-pose capture, then confirm motion mapping and controller requirements for your dexterous hand.
View VetraGlove Pro