Learning Inverse Kinodynamics for Autonomous Vehicle Drifting

arXiv:2402.14928v1 Announce Type: cross
Abstract: In this work, we explore a data-driven learning-based approach to learning the kinodynamic model of a small autonomous vehicle, and observe the effect it has on motion planning, specifically autonomous drifting. When executing a motion plan in the real world, there are numerous causes for error, and what is planned is often not what is executed on the actual car. Learning a kinodynamic planner based off of inertial measurements and executed commands can help us …

abstract arxiv autonomous autonomous vehicle cs.ai cs.lg cs.ro data data-driven error explore motion planning observe planning small type work world