Mia Patel

The assertion that grasping an apple is just a direct specialization of grasping a ball seems to have a 60% probability of being too simplistic.
Our priority should be that an apple, with its irregular shape and variable firmness (especially if it is a bit soft, as sometimes found at the market), requires much more nuanced sensor control.
The likelihood that a robot manages an apple bruised during transport optimally is low, much more complex than handling a rigid ball.
For example, a system trained for uniform balls could damage a fragile apple if pressure sensors are not recalibrated for the specific properties of fruits, a necessary update for real agricultural applications.

Claiming that the BionicSoftHand 2.0 system is a major driver of human-robot collaboration is complicating things unnecessarily. A robotic hand, even with its sensors and articulated movements, remains a tool. Collaboration is the complete organization that goes with it, not just cutting-edge technology; it's like having the best notebook doesn't guarantee my child will do their homework.

Training an AI model is like having a very detailed plan for a task, but without the resources to implement it. It is not enough for this Festo robotic hand to grasp a apple without damaging it; precise force sensors are needed for touch. Money and time are scarce commodities, and developing these sensors is a cost that must be justified. A significant investment is required to move from simple visual recognition to delicate physical manipulation. Without this budget, AI only "sees" the apple, it does not harvest it.

This is a good point regarding grants. It means that we really need to check the deadlines for regional funding requests because the envelope never lasts long. There isn't enough for everyone, and the first come, first served.

That the Festo Bionic Handling Assistant robotic system projects its logic onto agriculture seems very optimistic to me, as if the fruit harvesting problem was just a matter of robotic arms. Resources are finite, and the fact is that adopting this type of technology depends on many practical conditions to be effective. For it to truly work, one must consider the initial cost, integration into complex outdoor environments, and training personnel to use it. If farmers lack the budget to invest or the time to learn, all this beautiful system remains a laboratory prototype. For example, if energy costs skyrocket, it could make automation with such robots unsustainable economically.