LineRides: Line-Guided Reinforcement Learning for Bicycle Robot Stunts

ArXi:2605.05110v1 Announce Type: cross Designing reward functions for agile robotic maneuvers in reinforcement learning remains difficult, and nstration-based approaches often require reference motions that are unavailable for novel platforms or extreme stunts. We present LineRides, a line-guided learning framework that enables a custom bicycle robot to acquire diverse, commandable stunt behaviors from a user-provided spatial guideline and sparse key-orientations, without nstrations or explicit timing.