Sofia Patel

Frankly, seeing a Festo robotic hand hold a red ball, then an apple, and claiming it's just a « specialization » ignores the huge asymmetry between these two tasks to achieve maximum performance.
A ball is a perfect, rigid object; an apple has unexpected break points, a thin skin, and shape variations.
The true demonstration of dexterity would be to pick a fruit from a tree without damaging it, or to sort fruits efficiently and quickly on a conveyor, not just holding it.
This requires pressure sensors that adapt to the slightest defect, the ability to manage imperfection in reality, which holding a ball does not prepare for at all.
For a real productivity gain, a system that manages the uncertainty of each fruit, like an experienced farm worker, is needed.

Training an AI system to recognize an apple is indeed a prerequisite, but claiming it as the only condition for delicate manipulation by a robotic hand is a dangerous simplification. One must consider the failure threshold if force sensors or haptic feedback are absent; AI alone is not enough. Imagine planning an event where you know who is arriving (visual recognition), but without providing for chairs or suitable food (delicate manipulation): the final result would be a disaster, regardless of the guest list quality. The ability not to crush the apple depends on a multitude of technical conditions and not only visual recognition.

The idea that the mechanical flexibility of a robotic arm "unifies" vision systems seems a bit too optimistic.
Historically, the real challenge has never been the flexibility of the arm, but rather the system's ability to interpret what it sees and adapt to unforeseen situations.
We've always sought to improve the integration between perception and action, which involves vision algorithms and decision-making, not just mechanics.
It's like thinking that better wrist articulation would solve all my diagnostics; it's useful, but the real brain work is elsewhere.
Without a good understanding of the environment, even the most agile arm like that of the Bionic Handling Assistant remains limited when faced with a new obstacle on the assembly line.

Festo's hand's ability to grasp an apple without marking it is the pinnacle of robotics, far beyond simple ball grasping.
Reaching full potential requires constant adaptation to the complex geometry and firmness variations of a fruit, not just a basic grip.
It's the difference between doing the minimum and seeking excellence, like avoiding any bruising on a peach for sale, which is the real challenge.