{"id":812,"date":"2025-01-01T19:09:58","date_gmt":"2025-01-01T19:09:58","guid":{"rendered":"https:\/\/akaflieg.nl\/?p=812"},"modified":"2025-01-01T19:11:35","modified_gmt":"2025-01-01T19:11:35","slug":"2025-year-of-the-pathfinder","status":"publish","type":"post","link":"https:\/\/akaflieg.nl\/index.php\/2025\/01\/01\/2025-year-of-the-pathfinder\/","title":{"rendered":"2025: Year of the pathfinder"},"content":{"rendered":"\n

One day in 2009, I was lying in the grass near my dorm at the Twente University campus. I saw a DG-300 circle above me, which launched at the nearby airbase. Not long before I had learnt about the work of Alan Kay<\/a>, who’s team at Xerox PARC invented about half of what we call “Personal Computing” today. Their way of thinking was new and exiting to me. One thought-provoking question that had stuck with me was: “What would be ridiculous not to have in 25 years?”<\/strong><\/em><\/p>\n\n\n\n

The dream<\/h2>\n\n\n\n

Watching the DG-300 circle in a thermal, I thought: “It would be ridiculous<\/strong> not to have a precise prediction of thermals in 25 years”<\/em>. And so I started thinking….<\/p>\n\n\n\n

What would gliding be like if we could prevent out-landings? If we could precisely predict the weather? Predict where thermals will form, when they will form and how fast we can climb in those thermals? This would be a game-changer. No more need for sustainer engines. No more need for late-night retrieves. That sounds pretty great….<\/p>\n\n\n\n

Finding an exponential to make it happen<\/h2>\n\n\n\n

If we could use Moore’s law, this might not actually be that hard to achieve. In 25 years the amount of computing power on board of a glider will be a lot, about 100.000 times that of 2009. We can either use Moore’s Law to make the computers on board faster or to reduce it’s power consumption, or a bit of both. So even if batteries don’t scale exponentially in capacity over time, we can still use Moore’s Law to compute more for the same amount of energy.<\/p>\n\n\n\n

Make it feasible<\/h2>\n\n\n\n

But 25 years is a long time. It probably doesn’t take 25 years to develop a solution. I decided that weather models, such as WRF, would probably be too slow. I decided something based on observations <\/strong>would probably work better than something based on predictions<\/strong>. <\/p>\n\n\n\n

In 2009 cellular data wasn’t as ubiquitous as it is in 2025. My conclusion in 2009 was therefore: I should invest my time in Wireless Mesh Networking, so the gliders can communicate with each other without the need for cellular coverage.<\/em> And that’s what I did: I spent my Master’s Thesis on Wireless Mesh Networking for gliders. <\/p>\n\n\n\n

After finishing my thesis, I was not very content with the result. I started working, and the dream of live weather insights faded…. until I had access to the live tracking data from the SkyLines platform. When I looked at the SkyLines data around 2019, I saw that cellular coverage had dramatically improved. I could see that 97% of all GPS positions took less than 1 second to reach the SkyLines server. That means that the glider in question has a working cellular connection!<\/p>\n\n\n\n

First try<\/h2>\n\n\n\n

This lead to my first attempts. First, I used XCSoar’s thermal detection algorithm to locate thermals. A clubmate of me flew with a moving map that showed thermals, and found two where I predicted them. Nice!<\/p>\n\n\n\n

Then I started to look at faster cross country flights, and saw that a lot can be either won or lost during the gliding phase. I wrote a program that analyses OGN data and collects statistics of the entire world. I wrote another program that finds the fastest route from A to B given those statistics.<\/p>\n\n\n\n

A friend did an 750km attempt in his ASW24, and I followed him live during the attempt. This is what I saw during that day:<\/p>\n\n\n\n

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