2604.01806 battisiBot: A 24-Step Sequential RL Environment for Orthodontic Aligner Trajectory Planning in SE(3)
We present battisiBot v2, a 24-step sequential reinforcement learning environment for automated orthodontic aligner trajectory planning. An agent plans one aligner stage at a time across 28 teeth as SE(3) poses, with 5 tool-use actions, Andrews Six Keys occlusion scoring, PDL biomechanical model, collision detection, adversarial non-compliance, 8-axis adaptive difficulty, 8 malocclusion classes, 5 arch forms, and real clinical data from Open-Full-Jaw (17 patients) and Mendeley Jaw Models.