As you may already know, one of the projects that our developers worked on (the expert AI team at NTR Lab) was a project for drones that can work indoors. NTR Lab created unique, embedded software for UAV autonomous indoor navigation.
The original object of the SLAM method was quite narrow. But more and more, as this technology becomes popular and more applicable on practice, we are moving swiftly towards a future we watched in movies.
As you know, my company develops software and hardware for UAVs, but not the kind you usually read about.
While developing our indoor drone and the software for it, we faced and had to handle a lot of challenges, like these:
The drone doesn’t know where it is because there are no GPS signals in places like steel tanks, tubes, or certain kinds of rooms and that makes standard drone navigation impossible. Even when the drone has all the sensors needed to navigate obstacles, it’s still fairly useless unless it can place itself within the enclosure, whatever it may be.
Frequently UAVs cannot be controlled over ordinary radio channels, because of surface reflection, which makes the need for “autonomous and unmanned” even more important. However, when dealing with various surfaces one size does not fit all, because each surface requires different custom features. And that’s why indoor drones stay indoors.
Today’s cameras create amazing images, but they all have one thing in common: they require light to create images. The lack of sufficient light in tanks, tubes, etc., makes producing good images extremely challenging.
UAVs are reliant on magnetometers when operating in places where GPS doesn’t work. However, magnetometers don’t always operate correctly; for example, electric motors generate strong magnetic fields and large chunks of ferrous metals can also affect the field.
While drones are highly maneuverable they require space in which to do it. While they have no problem outside, it is much more difficult to fly in a tight, enclosed space, such as a tank or tube.
Flying a UAV in the open air, or an empty room with plain surfaces, is very different from flying an environment full of edges and obstacles. Indoor navigation demands precise positioning to handle working goals, such as inspections, etc., as previously discussed. Edges and obstacles demand special technologies, such as SLAM, but they require substantial, additional hardware that adds weight. Because indoor drones are required to fly and maneuver in tight spaces can be neither large nor heavy.
Please join me next week to learn about the various approaches that address these challenges.
Also, if you know of other challenges, please share them in Comments and I’ll do my best to address them, too.
