This is a great introduction to all the technology that people have developed over the years (since the 1970's!) to make robots autonomous, that, unfortunately, have never quite worked. As I like to point out, if we knew how to make drones (or any kind of robot) really, actually autonomous you'd see them used first of all in Ukraine, and recently in Lebanon. You don't, all the drones used in warfare are remote-controlled. Autonomy doesn't work yet. Not well enough to deploy in a theater of war.
Btw, I did really enjoy the graphic sumarising Control Theory. I'd criticise the lack of Planning and Scheduling, i.e. the PDDL-based symbolic AI stuff which is the technology that works best and is used e.g. by NASA on Perseverance, but OK, there's basically three communities that attack the same problem from different angles: Model Predictive Control, Planning & Scheduling, and RL. Two out of three is not too bad (but I don't see how RL goes under CT; never mind).
"You don't, all the drones used in warfare are remote-controlled."
Is this really true. My (admittedly) naive understanding was that in a first phase radio remote controlled drones were used. Then jamming became widespread and they tried to counteract with fiber-optic drones but they never caught on.
I thought that since we see more drones then ever now it must be a hint that most of them must autonomous to some degree now.
It does not seem that the author cites the source of the control theory map. It was created by Brian Douglas [1], an engineer whose YouTube videos [2] are great for learning core topics.
Also useful is Steve Brunton's channel [3]. He has a freely available book [4] co-authored with Nathan Kutz that ties machine learning and control.
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[ 4.6 ms ] story [ 34.2 ms ] threadBtw, I did really enjoy the graphic sumarising Control Theory. I'd criticise the lack of Planning and Scheduling, i.e. the PDDL-based symbolic AI stuff which is the technology that works best and is used e.g. by NASA on Perseverance, but OK, there's basically three communities that attack the same problem from different angles: Model Predictive Control, Planning & Scheduling, and RL. Two out of three is not too bad (but I don't see how RL goes under CT; never mind).
Is this really true. My (admittedly) naive understanding was that in a first phase radio remote controlled drones were used. Then jamming became widespread and they tried to counteract with fiber-optic drones but they never caught on.
I thought that since we see more drones then ever now it must be a hint that most of them must autonomous to some degree now.
Also useful is Steve Brunton's channel [3]. He has a freely available book [4] co-authored with Nathan Kutz that ties machine learning and control.
[1] https://engineeringmedia.com/ [2] https://www.youtube.com/@BrianBDouglas [3] https://www.youtube.com/@Eigensteve [4] https://news.ycombinator.com/item?id=36374528