When I was still in high school, as a science project, we wanted to launch a stratospheric balloon to get pictures from "the edge of space". But the first thing you learn on the internet when you are preparing such an experiment is that the recovery is often super hard. It could lands dozens of kilometers away, in a tree, a lake, on a road, in the middle of a city.
So I told to myself that if we end up launching this balloon we need a system to make sure the recovery is easier. In other words, a system to guide our payload back to a precise landing point.
That was 3 years ago and as I write these lines we're getting ready for the first high-altitude test flight(s) :)
The end goal of my project is to make meteorological radiosondes reusable by bringing back to a precise landing point where their recovery is super easy. It works by deploying a steerable parachute, a parafoil, as the radiosonde is getting back to the ground after the balloon bursts at an altitude of 30km.
As soon as we demonstrate that the system can be deployed from 30km and we can bring back a small meteorological radiosonde, we can also help deliver a whole range of other payloads such as emergency medical kits in remote areas deployed from another UAV or a small airplane.
We can also dream higher, why not make some satellites reusable? Why not simplify the recovery of material coming down from the ISS or from Mars?
The most important thing that I've learned with this project is the need to fail to learn. I will remember for a long time the very first drop test where everything, every single piece of the system failed. The funny thing when you work with a parachute system is that when it fails, it doesn't fail-safe. So you have to rebuild everything and any piece of data you can get from the test gets super valuable.
It took me about two years of drop tests, maybe about 50 of them, before getting a working prototype. If you are afraid to test and fail you never learn. I'm now actually very afraid when it works on the first try because I know it means I haven't yet discovered the problem that is going to appear on the second or third test.
Understanding how the climate is changing is the key to making sure we adapt our society as well as possible and correct our mistakes where we can have a greater impact. Meteorological radiosondes are by far the first data input used to create and improve the meteorological and climate models used every day to understand the current change.
If we can make radiosondes cheaper by making them reusable when getting more data for the same cost. Getting more data means a greater model, which means a greater understanding means a greater adaptation.