He taught his bot, Arty to feel the terrain.
Shifting from absolute coordinates to relative sensing gives your bot actual perception. White Puma’s ray-casting wall-off works on a three-step sensory loop:
1. Anchor to a dynamic known. Arpy starts the calculation at the natural expansion, a point that reliably exists on every map.
2. Sweep for the boundary. Arpy casts rays 100 degrees from the natural toward the map center, sweeping the terrain.
3. Measure the delta. Arpy hunts for the math. It finds the sudden jump in distance where the terrain drops off. That delta is the choke point.
Arpy handles narrow ramps, wide ramps, and flat ground equally well. The bot simply feels the space around it.
Seeing White Puma’s process reminded me why we stick to these principles. His first bot was completely hardcoded, and he is aggressively undoing that to make it dynamic.
We are building autonomous agents. Bots are like children. When we give them the answers, we deprive them of the learning. We strip away their ability to engage with their environment, making them dependent on us. That’s not autonomy.
Building sensory loops immunizes your code against ladder updates. You solve for the space itself.
