Planning Dynamically Feasible Trajectories for Quadrotors Using Safe Flight Corridors in 3-D Complex Environments

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 人工智能 数学 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 [Institute of Electrical and Electronics Engineers]
卷期号:2 (3): 1688-1695 被引量:435
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.
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