The idea that a flexible articulated arm could solve software fragmentation in robotic vision systems lacks empirical evidence. We need observable metrics to show that mechanical design affects sensor integration or algorithm quality.
What is the threshold of flexibility required, and how does it translate into a measurable improvement in object recognition accuracy?
Without a comparative study with a significant sample (n= ?), demonstrating a reduction in software fragmentation through this flexibility, it remains an untested hypothesis.
For example, a robot with a more flexible arm wouldn't necessarily see better a poorly printed label on a package; that depends on vision algorithm quality, not arm flexibility.