Learning motion primitives for planning swift maneuvers of quadrotor

• Main Authors: Camci, Efe, Kayacan, Erdal
• 其他作者: School of Mechanical and Aerospace Engineering
• 格式: Article
• 語言: English
• 出版: 2020
• 主題: Engineering::Mechanical engineering; Reinforcement Learning; Motion Planning
• 在線閱讀: https://hdl.handle.net/10356/143523

This work proposes a novel, learning-based method to leverage navigation time performance of unmanned aerial vehicles in dense environments by planning swift maneuvers using motion primitives. In the proposed planning framework, desirable motion primitives are explored by reinforcement learning. Two...