I was working on the Air Traffic Control side of unmanned free balloons in 2020, and Loon was an exciting project. While it's a shame it wasn't financially viable, they had it working with up to 60-ish balloons in the stratosphere at any given time. This was an amazing accomplishment.
The navigation was equally amazing. It was Loon who did some real research on stratospheric weather. While many meteorological entities throughout the world knew and understood tropospheric weather, the stratosphere was mostly unknown. In addition to AI, Google really did expand the knowledge and science of stratospheric weather.
I knew some friends over at Loon and one of their challenges was it wasn’t highly deterministic where the balloon would land at the end of life, and they had a rescue team with speedboats, helicopters and land rovers to go recover balloons. They could pick a big enough radius and have it land somewhere within that to avoid cities, and human settlements.
Also, Alphabet burned considerable money on this for 9 years before shutting down. Not sure if it’ll come back, at least not by Alphabet.
We can control systems that have not only fluid-mechanical, but also heat transfer and chemical reactions, all happening at the same time with huge bars of uncertainty.
Next.
The baseline comparison is not meant to be some final word on any given controller. In this case they clearly cite it to a particular paper. [1]
1: https://github.com/google/balloon-learning-environment/blob/...
They compared against another bad RL system and they are better than that.
That is far from an "expert control system"
