Capture
Record synchronized physical interaction.
Technology
From human interaction to reusable machine skill.
PlainHand is building an integrated training and data system in which every layer has to earn the next.
CURRENT WORK + STAGED ROADMAPIntegrated system
Research becomes infrastructure when the evidence holds.
The technology story is a sequence, not a collection of disconnected features.
Evaluate
Find useful complete events and smaller parts.
Weight
Adjust sensor influence as usefulness changes.
Measure
Test matched outcomes and preserve uncertainty.
Transfer
Challenge the effect on new models and conditions.
Sense
Build new instrumentation only when evidence justifies it.
Compound
Feed richer human, robot, failure, and correction data back in.
Moment-to-moment information
Every sense stays available. Influence can change.
A grasp may rely on vision during reach, distance during approach, force at touch, and vibration during slip. Phase One tests this idea offline; live execution remains a later hypothesis.
Explore Adaptive Sensor AttentionSelective hardware
Hardware as a data-generation instrument.
PlainHand can remain a training-layer company while building the selective physical infrastructure needed to test it.
POST-PHASE-ONE
Staged sensing glove
Candidate modalities must earn retention through measurable incremental value, reliability, synchronization, wearability, safety, cost, and complexity.
FUTURE ROADMAP
Robot-native data instrument
A hand prototype may be scientifically valuable before commercial maturity if it generates interaction data that advances the learning program.
From signal to structure
Many separate senses. One coherent physical record.
Vision, contact, force, pose, and motion arrive as separate streams. The technology stack aligns them in time, tests which of them carry the useful information, and turns the result into structure a model can learn from.