运动规划
线性不等式
计算机科学
机器人
数学优化
弹道
多面体
线性规划
人工智能
数学
算法
天文
几何学
不平等
物理
数学分析
作者
Sikang Liu,Michael Watterson,Kartik Mohta,Ke Sun,Subhrajit Bhattacharya,Camillo J. Taylor,Vijay Kumar
出处
期刊:IEEE robotics and automation letters
日期:2017-02-07
卷期号:2 (3): 1688-1695
被引量:384
标识
DOI:10.1109/lra.2017.2663526
摘要
There is extensive literature on using convex optimization to derive piece-wise polynomial trajectories for controlling differential flat systems with applications to three-dimensional flight for Micro Aerial Vehicles. In this work, we propose a method to formulate trajectory generation as a quadratic program (QP) using the concept of a Safe Flight Corridor (SFC). The SFC is a collection of convex overlapping polyhedra that models free space and provides a connected path from the robot to the goal position. We derive an efficient convex decomposition method that builds the SFC from a piece-wise linear skeleton obtained using a fast graph search technique. The SFC provides a set of linear inequality constraints in the QP allowing real-time motion planning. Because the range and field of view of the robot's sensors are limited, we develop a framework of Receding Horizon Planning , which plans trajectories within a finite footprint in the local map, continuously updating the trajectory through a re-planning process. The re-planning process takes between 50 to 300 ms for a large and cluttered map. We show the feasibility of our approach, its completeness and performance, with applications to high-speed flight in both simulated and physical experiments using quadrotors.
科研通智能强力驱动
Strongly Powered by AbleSci AI