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Comment by whatever1 | Hacker News Reader

Not sure if I buy the argument that touch sensitivity is a prerequisite for dexterity.

I can put on a thick glove (losing touch and pressure sensitivity all together) and grab a fragile glass without breaking it.

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Because you have learnt it already and you can make predictions. And you don’t lose pressure sensitivity, you still feel the pressure of your hand to the glove, a better example would be using an exoskeleton or robotic arm or inactivate certain nerves. Still you risk more of breaking it imo and you have to be more careful in the beginning until you learn again.

Edit: and you probably are not gonna be as fast doing it

You don't lose pressure or touch sensitivity from wearing even thick welding gloves. You can still feel how hard you are gripping the rod quite easily.

The same is true for a motor controller.

Depends heavily on the use case. Indeed many tasks humans carry out are done without touch feedback - but many also require it.

An example of feed-forward manipulation is lifting a medium-sized object. Classic example is lifting a coffee cup. If you misjudge a full cup for empty you may spill the contents before your brain manages to replan the action based on sensory input. It takes around 300ms for that feedback loop to happen. We do many thing faster than that would allow.

The linked article has a great example of a task where a human needs feedback control: picking up and lighting a match.

Sibling comments also make a good point on that touch may well be necessary to learn the task. Babies do a lot of trial-and-error manipulation and even adults will do new tasks slower first.

The industry's approach to "trial and error to learn the task" is to have warehouses of robots perform various tasks until they get good at them. I imagine that you'd rely on warehouses less once you have a real fleet of robots performing real tasks in real world environments (and, at first, failing in many dumb and amusing ways).

Robots can also react much faster than 300ms. Sure, that massive transformer you put in charge of high level planning and reasoning probably isn't going to run at 200 tokens a second. But a dozen smaller control-oriented networks that are directly in charge of executing the planned motions can clock at 200 Hz or more. They can adjust fast if motor controllers, which know the position and current draw of any given motor at any given time, report data that indicates the grip is slipping.

Only because of your training otherwise.

This is a good point, but I’m not convinced it negates the author’s argument.

Consider whether you could pick up that same fragile glass with your eyes closed? I’d wager you could, as you’d still receive (diminished) textile feedback despite the thick gloves.

What about full control of a claw machine to pick up said glass?

The scientists at Oak Ridge National Labs develop a lot of dexterity working with robotic manipulators in the radioactive hot cells there

https://youtu.be/B-Lj7xAXJpc

If I can see the said glass, absolutely. I can even do it remotely.

And yet, when you pick up a glass expecting it to be full but it turns out to be empty, you'll overdo the motion; part of dexterity is expectations.

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