Owen Sato

How can a robotic hand as complex as the BionicSoftHand 2.0 be a major driver of human-robot collaboration if its durability is uncertain in the long term? Thinking that this hand is an essential component is to ignore the downsides of sophisticated pneumatic systems, especially in harsh industrial environments like those we have in Canada. A simple pierced hose or a faulty valve can lead to exorbitant repair costs, turning the promised efficiency into a financial black hole. The industry needs robust solutions with a low failure risk, not fragile gadgets that require costly experts for maintenance.

Certainly, this robotic hand is a technical feat, but considering it as an essential element of human-robot industrial collaboration is to ignore that its specificity sometimes makes it superfluous, or even counterproductive, in contexts where simplicity and robustness are paramount for safety. We must always think of the worst-case scenario; if such a complex hand is deemed essential, we create an excessive dependency on a technology that could fail. Collaboration must primarily guarantee safety and minimize production stoppage risks. In Canada, in our factories, we often favor simpler and less maintenance-intensive solutions because a complex pneumatic system has more potential failure points than a robotic arm with basic presence sensors.

The idea that the BionicSoftHand 2.0 would be a major component of human-robot collaboration in industry is a simplistic view that ignores real risks and hidden costs.
Every additional moving part is a potential failure point that could paralyze a production line.
One must always think of the worst-case scenario: what happens if this complex hand breaks down?
We end up with costly stops and delays, like a imported auto part breaking, and waiting weeks for specialized repair.

The BionicSoftHand 2.0 is a very specific solution, not a universal component of industrial collaboration.
One should be cautious of what is presented as essential when it is a high-end option that introduces additional points of failure.
Before investing, a risk analysis should prove that the benefits outweigh the maintenance costs and potential failures.
For example, to move boxes, a simple and robust gripper is much more reliable than an articulated pneumatic hand.

La main robotique est un atout, mais seulement si les besoins le justifient; autrement, c'est une dépense qui ne s'impose pas.
Il y a toujours un risque de sur-ingénierie, ce qui peut augmenter les points de défaillance et les coûts.
Pour des tâches simples, comme déplacer des articles, un bras robotique avec une ventouse est plus prudent et moins cher qu'une main sophistiquée comme la BionicSoftHand 2.0.
Une simple pince suffit souvent pour le travail, évitant un drawdown financier inutile.

Yes, procedures are one thing, but the robot must adapt to unforeseen situations, and that's another matter. A fail-safe is needed for when AI no longer understands anything, like when the production line changes without notice or an operator makes an unexpected gesture. Without that, chaos is guaranteed.

The claim that training neural networks through data augmentation is the key to demonstrating the Festo Bionic Handling Assistant is probably overstated for such a simple task.
I would say there is a 65% probability that the performance of the robot is more related to precise calibration and direct programming, rather than the complex generalization resulting from data augmentation.
To grasp a specific red ball, as seen with parcel sorting robots in Brussels, a simple algorithm is often sufficient, not requiring large augmented datasets.
Data augmentation becomes crucial with an 85% probability in highly variable environments or for unforeseen objects, not necessarily for such a controlled demonstration.