弹道
计算机科学
运动规划
贝塞尔曲线
分段
多项式的
基础(线性代数)
伯恩斯坦多项式
路径(计算)
欧几里德距离
快速行进算法
计算机视觉
领域(数学)
人工智能
数学优化
应用数学
数学
算法
机器人
物理
数学分析
程序设计语言
纯数学
几何学
天文
作者
Fei Gao,William Wu,Yi Lin,Shaojie Shen
出处
期刊:International Conference on Robotics and Automation
日期:2018-05-01
卷期号:: 344-351
被引量:237
标识
DOI:10.1109/icra.2018.8462878
摘要
In this paper, we propose a framework for online quadrotor motion planning for autonomous navigation in unknown environments. Based on the onboard state estimation and environment perception, we adopt a fast marching-based path searching method to find a path on a velocity field induced by the Euclidean signed distance field (ESDF) of the map, to achieve better time allocation. We generate a flight corridor for the quadrotor to travel through by inflating the path against the environment. We represent the trajectory as piecewise Bézier curves by using Bernstein polynomial basis and formulate the trajectory generation problem as typical convex programs. By using Bézier curves, we are able to bound positions and higher order dynamics of the trajectory entirely within safe regions. The proposed motion planning method is integrated into a customized light-weight quadrotor platform and is validated by presenting fully autonomous navigation in unknown cluttered indoor and outdoor environments. We also release our code for trajectory generation as an open-source package.
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