Recent developments in computer vision have often relied on access to big data, powerful
compute, or both. City-based systems, such as self-driving cars and airport checkpoints, have
benefited greatly from these advances, so much so that automated cars and security checks
are beginning see true deployment in modern society. In contrast, robots and autonomous
systems in data- and compute-constrained environments, like remote wilderness regions or
off-Earth, are still relying on pre-deep learning era computer vision algorithms. Robots in
the most challenging of environments — and, correspondingly, the environments
that require the highest level of autonomy for robots — have been left behind by
modern computer vision.