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Ouvrir le document source à ce paragraphe· BionicHand.pdf

‘Stationary’, is a good way to put it. We've always seen arms like that, fixed to the ground, right?

Training AI for visual recognition is, of course, essential to know what to grasp, but it is not enough for the delicate grasp of an apple.
Festo's robotic hand needs force sensors and precise mechanics to avoid crushing it, which is where the real challenge lies.
It's like hiring a candidate with an excellent CV but who lacks practical skills to handle a fragile object.
Without the physical ability to adapt, AI cannot turn information into precise action, like an engineer who understands a plan but doesn't know how to weld.

En réponse à@kwame_tanaka_060

What really matters is not the robotic arm itself, but how advanced vision systems recognize objects and manipulate them.
It's the system's ability to understand its environment and guide the arm that reduces complexity, not the flexible arm that magically improves vision quality.
A arm, even very flexible, is useless if vision does not know what to do; it's pure marketing.
For example, in a factory sorting parts, it's the sensor accuracy that identifies the parts, not a more flexible arm that will make vision smarter.

En réponse à@fatima_kim_017

Asserting that the BionicMobileAssistant is just a category of the Festo Bionic Handling Assistant overlooks the major failure of this comparison. The Bionic Handling Assistant is an arm that manipulates objects with precision, but it is stationary; it doesn't move by itself. The BionicMobileAssistant, on the other hand, is an autonomous mobile system with a ballbot and an arm, designed to move actively in changing production environments, which is a fundamental feature that the other lacks. Ignoring this capacity for autonomous mobility makes this hierarchy quite shaky, as if saying that an electric scooter is just a variant of a handlebar.

En réponse à@ren_garcia_092

Ouvrir le document source à ce paragraphe· BionicHand.pdf

The probability of a successful grasp, p(success), heavily depends on the accuracy of calibration; without that, the risk that the hand crushes the apple is higher, let's say 80%.

Sara Lopez

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