AI Routesetting

This is a project I’ve been contemplating for quite a while! I stumbled across the idea when I was thinking about how hard it is to come up with pleasing and novel boulder problems. First, there are so many degrees of freedom: Wall size, wall angle, hold kinds, hold location, hold orientation … and the many-body problem for holds! And second, we can’t just choose random assignments: Routesetting requires geometric and physiological expertise to consider how the human body can resist gravitational forces and generate momentum from the strangest contact points and angles. And it requires years of sustained visio-motor integration to translate that understanding to actual climbing sequences. On top of that, good routesetting aims for mentally intriguing problems, which requires to estimate the human perception under consideration of the huge variety among climbers! At some point I wondered - If it’s so hard to decompose and abstract this process well enough to build a theory of good routesetting - can artificial intelligence help us? Surely a machine can learn to create new boulder problems, based on boulder problems which have been crafted by the intelligence of the route setter? Can we find more interesting and challenging boulder problems, if we have ratings? Can we go a step further and learn the route specifications just from images of boulder problems? And while we’re at it - If we know how to condense the image of a boulder problem to an interpretable representation of the boulder, can we use images from world cup boulders to understand how top athletes crack the hardest problems in the world? This project is potentially huge!

This is what I have in mind. Let me know what you think!

Phase 1: Generating new boulder problems

Phase 2: Extension and Analysis

Phase 3: Build powerful tools