Deep Convolutional Networks as the New Substrate for Robotic Perception

Veyrum Research · Veyrum Retrospective · set in 2013 · written 2026-09-01

A retrospective set in 2013 examining the then-emerging case that learned convolutional features would displace hand-engineered pipelines in robotic perception.

Summary

DRAFT — not for publication. Veyrum Retrospective: written 2026, examining the 2013 frontier. Not published in 2013.

In 2013, robotic perception was dominated by hand-crafted features. This paper reconstructs the then-radical thesis that end-to-end learned representations would become the dominant substrate.

Why it was cutting-edge in 2013

Convolutional approaches had just broken open large-scale image recognition; crossing into robotics was unproven.

References

[NEEDS-VERIFICATION] Contemporaneous (~2013) primary sources — to be grounded by Scout before publication.