Robotics is hard. And creating, operating, and scaling a robotics business is even harder. Not only is your agility in testing market fit handicapped by the fact that your product involves hardware that isn’t easily changed; you also realize quickly that “everything” in Murphy’s Law means everything, and hardware failures, which require an engineer to fly somewhere to fix a robot, are only a small part of that.
And then there is software. For your fleet of robots to function and for you and your team to deploy, operate, and maintain it, a lot of software is required. ROS, the…
There are situations where things seem to be going well and you can pretend to yourself and those around you that you are doing well for quite a bit longer even though utter failure is unavoidable. This is one aspect of “failing fast”: ask the hard questions first!
In many cases of decision making, it is impractical to plan ahead for every step along the way to ones goal. This is particularly true when there is a lot of uncertainty about the future, as for instance caused by adversarial actors. In these cases, where the space of possibilities that would need to be considered exceeds one’s ability to process them all, the common approach in AI is to use heuristic evaluations of some future situations that seem reachable — they are on the horizon—, and then decide based on those evaluations which strategy to follow in the short-term…
Christian Fritz
CEO of Lumin Robotics; Former VP of Software at Savioke; PhD in CS/AI from UofT.
