· 5 min read
From Resistance to Holding Charge
Our second-generation tactile sensing material holds charge instead of changing resistance, giving a cleaner baseline, more signal at light contact, and manipulation data you can trust across a full working shift.
Our second-generation sensing material holds charge. It replaces a film that reported touch by changing resistance under load, and the difference shows up exactly where it matters: on a hand that has been working for hours.
The first generation did its job. It went onto a glove, it went onto a robot, and it proved that a conformable film could carry full-surface tactile signal from a human demonstration through to a robot manipulation policy. It also showed us where the ceiling was.
What the first material taught us
The ceiling never showed up on the bench. On a bench a resistive film looks clean. It shows up on a working hand, as four problems that compound.
- Drift over long wear. The baseline a reading is measured against does not stay put across a long session. Correct for it and you are correcting against an estimate. Leave it and a slow change in grip looks like the sensor settling.
- Hysteresis after repeated loading. Load the same site twice and the second reading is not the first. Across a shift of repeated grasps, that memory accumulates.
- Signal to noise at light contact. The informative part of a manipulation is often the lightest part. That is exactly where a resistive response is weakest and the noise floor is nearest.
- Environment on a worn glove. A working hand gets warm and damp, and a material whose resistance answers to load answers to that too. Separating them afterwards is possible, but never free.
Each is manageable alone. Together they cap how much of a recording you can trust without someone watching it happen. For a company whose product is manipulation data, that cap is the whole business.
From responding to holding
The first material reports touch by changing how much it resists current under load. The second reports touch by holding charge. The distinction sounds small. It changes the shape of the signal.
A resistive response exists only while the load exists. It is a continuous readout of a continuously applied force, and it inherits everything that drifts between the material and the converter. A charge-holding response works differently. Contact does work on the material, the material accumulates the result, and it holds that state instead of relaxing the moment the load comes off.
That is as far as we will go on principle. The material itself, and how it is made, stays in the building.
A load is applied twice: once firm and held, once light and brief.
A response that only reacts while loaded tracks the press, lags at both edges, and relaxes to a baseline that has moved. The light contact almost disappears.
A response that holds charge takes a sharp edge at contact, stays flat while the load is held, and returns to the baseline it started from. The light contact is unambiguous.
The difference lives in what happens after the load comes off. A resistive response relaxes toward a baseline that has moved. A charge-holding response returns to the one it started from.
What it changes in practice
Four things change on a glove across a working shift.
- A session holds its zero. The baseline stays where it was put for a full shift. No per-session recalibration, and nobody has to stand over a glove to know whether its data is worth keeping.
- Light contact becomes usable. Contacts that used to sit inside the noise floor now arrive as separable events: the brush before a grip closes, the small slip that says an object moved in the hand. That is the part of a manipulation carrying the most information about how it was done.
- Onset resolves as an edge. Contact begins as a step rather than a ramp, so the instant a grasp closed can be placed in the record directly instead of inferred from the shape of a curve.
- Grasps stay comparable. The same grasp made at the start of a shift and at the end of one reads the same way, which is what lets hours of collected contact pool into a single dataset.
Those four are one property described four ways. The second material spends far less of its output describing its own condition, and what is left is a description of what the hand actually did. That is the only part that survives into a training set.
Why this matters at scale
Our premise is that the sensor on the human hand and the sensor on the robot should be the same sensor. A film that drifts undermines that quietly. If a glove’s zero moves across a session and a robot’s moves differently, the two stop reporting the same quantity, and the retargeting problem you thought you had removed reappears as a calibration problem. Holding a stable zero is what makes cross-embodiment transfer hold up outside a demo.
The rest is about people rather than physics. A sensor that needs supervision caps your collection at the number of technicians you can put in a room. A sensor that holds its own baseline does not.
The question was never how much contact we could record. It was how much of it we could still believe eight hours later.
A tactile stream you can trust unsupervised is one half of a usable record. The other half is making sure it lines up with what the hand was doing and what it was doing it to, which is why our glove captures touch, anatomical hand tracking and vision on a single clock.
Both halves are working. Our second-generation material is successfully capturing clean, poolable contact data across full working shifts, on real hands doing real tasks, with nobody standing over it. Manipulation data is the binding constraint on robot learning today, and this is how we lift it.
If you are building humanoids, prosthetics, or any system that learns dexterous manipulation from real-world contact, we would love to hear from you.
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