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Curious, could you not calibrate using a force sensor, then include the output as a learning parameter. This seams a naive approach, which likely means it has been tried early on with other low hanging fruit, but I'm curious what the analysis of that approach is. Is there a fundamental reason this wouldn't work?

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You could, and this is what we did with ReSkin, https://ReSkin.dev

The reason we don't want to do this is that it is difficult to cover all possible characteristics. Say we do single point contact localization, and 3-axis forces prediction. What happens when we have multi-point contact? The calibration has only been used to calibrate/align in a lower dimensional space. This is primarily why not needing calibration and baking this into the hardware is a lot more appealing. The user/designer no longer needs to think about the task and the dimensions of alignment required for that task.

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