最大值和最小值
稳健性(进化)
轨迹优化
计算机科学
弹道
路径(计算)
水准点(测量)
数学优化
拓扑(电路)
算法
数学
最优控制
地理
计算机网络
基因
组合数学
物理
数学分析
生物化学
化学
大地测量学
天文
作者
Boyu Zhou,Fei Gao,Jie Pan,Shaojie Shen
标识
DOI:10.1109/icra40945.2020.9196996
摘要
Gradient-based trajectory optimization (GTO) has gained wide popularity for quadrotor trajectory replanning. However, it suffers from local minima, which is not only fatal to safety but also unfavorable for smooth navigation. In this paper, we propose a replanning method based on GTO addressing this issue systematically. A path-guided optimization (PGO) approach is devised to tackle infeasible local minima, which improves the replanning success rate significantly. A topological path searching algorithm is developed to capture a collection of distinct useful paths in 3-D environments, each of which then guides an independent trajectory optimization. It activates a more comprehensive exploration of the solution space and output superior replanned trajectories. Benchmark evaluation shows that our method outplays state-of-the-art methods regarding replanning success rate and optimality. Challenging experiments of aggressive autonomous flight are presented to demonstrate the robustness of our method. We will release our implementation as an open-source package 1 .
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