Sampling-based Motion Planning for Uncertain High-dimensional Systems via Adaptive Control скачать в хорошем качестве

Sampling-based Motion Planning for Uncertain High-dimensional Systems via Adaptive Control

Title: Sampling-based Motion Planning for Uncertain High-dimensional Systems via Adaptive Control Authors: Christos K. Verginis, Dimos V. Dimarogonas, Lydia E. Kavraki Abstract. We consider the problem of safe motion planning for high-dimensional robots with uncertain dynamics by integrating sampling-based motion planning with adaptive feedback control. We develop a feedback control scheme that tracks a given reference trajectory within certain bounds, while simultaneously compensating for dynamic uncertainty. Employing this result, we cast the problem of kinodynamic motion planning to a geometric one, which can be usually solved more efficiently. Intuitively, we use a geometric planner to obtain a high-level safe path for the robot, and a low-level adaptive feedback control algorithm to execute it while taking into account the robot dynamics. Keywords: motion planning, adaptive control, robotic manipulators, uncertain dynamics