Gloves & wearables
Gloves (and hand trackers) translate human motion into robot commands. The hard parts are calibration, latency, and mapping human kinematics to different robot hands — covered in demonstration data and Communication & architecture.
Motion sketch: stylized fingers (CSS) — same idea as dexterous hands, but here the story is human → robot mapping.
Learning outcomes
- Explain calibration, latency, and retargeting for human → robot mapping.
- Compare gloves-only vs headset-mediated teleop for your setup.
- Collect episodes with timestamps suitable for downstream learning.
Learn
Hand tracking pipeline, mapping DOF, safety envelopes.
Practice
Measure latency in open air; retarget to sim with matched DOF.
Challenge
One hardware session with speed caps + estop drill; post metrics on the Forum.
Facilitation: Run sim-only first; pair with demonstration data for episode hygiene.
Self-check
What goes wrong if latency is ignored?
Oscillation, poor contact control, and unsafe corrections — always show numbers early.
Why shared timestamps?
Vision, proprioception, and commands must align for imitation and debugging.
STEM alignment: human–machine interfaces, measurement, iterative design under safety constraints.
Practice drills
- Track hands in open air with visible latency metrics.
- Retarget to a simulated robot hand with matched DOF.
- Move to hardware with conservative speed limits and e-stop drills.
- Record episodes with shared timestamps for learning pipelines.
VR headsets vs gloves-only
Headsets add scene context but another latency path. Gloves-only can be lower friction for bench arms if you already have global cameras for world frame.