hic
A technical question: To scan a surface precisely, I'd rather put switches on the end effector aside the sensor, such that the arm places itself roughly above the surface to scan, pushes until the switches trigger, and scan keeping the switches on. A simple touch sense, basically. All trad robotics that smoothly follows many flat and curved surfaces. Not at all against AI here, it seems the whole thread is a constructive approach mixing the best tools to concrete targets. Not viable approach in your scenarios?
Thoughts on your concluding questions:
> where the abstraction boundary in robotics should sit. What should come from the robot manufacturer, what belongs in an application layer, and what will inevitably remain specific to the facility?
I really like when there is a "double SDK", with a low level one to target actuators and sensors individually (motor 2 of leg 4), and a higher level one with pre-defined scenarios (move forward, whatever the bot is a bipede, a quadcopter or a slug). These two API types often allow for easier work at the application layer. The SDK is also the main specific software that remains with the maker (facility?)
> industries where you've seen physical inspection tasks that look trivial to a person but are surprisingly difficult to automate
Too often a problem I have seen is... elevators. More generally unstructured environment, and environments explicitly tailored for humans. Proposals range from wireless interfaces (and so HW infrastructure dependent and hard to scale), to adding a manipulator to, say, push buttons on an elevator (and this means extra software to manipulate, recognise buttons, etc).
When we can control the environment precisely, we should as it simplifies so much---we can clip the world to platonic geometries and apply common tricks and trigonometry.
But when we cannot control the environment, really really much harder. Self-driving cars are a good example how hard it is, and still mainly focusing on relatively structured environments like cities.
Arbitrary environment is really where many expect AI/ML/probabilistic robotics to bring some necessary flexibility. And still out of reach today, except some astonishing use cases like Roombas (well, more like a best effort approach, still).
(please let me emphasize this "reptile" autonomy is today perhaps the hardest/time-consuming part killing many startups, as you nicely explain in the OP---Moravec's paradox)
--- The books I refer to include Pollan's recent book (cited several times in this thread), some of Grof publications, "A Really Good Day" by Ayelet Waldman, a plethora of "reports" from people's experience on Medium, and preview on Consciousness Medicine from Françoise Bourzat.
Is the scenario in the Interstellar movie unfolding before our eyes?