四轴飞行器
无人机
计算机科学
弹道
控制工程
控制理论(社会学)
模拟
人工智能
实时计算
航空航天工程
工程类
遗传学
物理
控制(管理)
天文
生物
作者
Mingyang Wang,Qianhao Wang,Ze Wang,Yuman Gao,Jingping Wang,Can Cui,Yuan Li,Ziming Ding,Kaiwei Wang,Chao Xu,Fei Gao
出处
期刊:Science robotics
[American Association for the Advancement of Science]
日期:2025-04-16
卷期号:10 (101)
标识
DOI:10.1126/scirobotics.adp9905
摘要
Quadcopter drones are capable of executing complex aerobatic maneuvers when controlled manually by skilled pilots but are limited to simple aerobatic actions when flying autonomously in open spaces. As such, this study introduces a comprehensive system that enables drones to generate and execute sophisticated aerobatic maneuvers in complex environments with dense obstacle distributions. A universal representation is proposed, succinctly capturing flight as a series of discrete aerobatic intentions. These intentions consist of topology and attitude changes, which can be combined in various ways to describe intricate flight maneuvers. A spatial-temporal joint optimization trajectory planner is also introduced to generate dynamically feasible trajectories that are as smooth as possible and devoid of collisions. In addition, we investigate unique yaw sensitivity issues in aerobatic flight and identify the inherent influence of differential flatness singularities on yaw rotations while avoiding associated dynamics issues. A series of ablation studies confirmed the necessity of these spatial-temporal joint optimization and yaw compensation strategies. Additional simulations and physical experiments validated the stability and feasibility of our proposed system for improving uncrewed aerial flight. The proposed system enables drones to autonomously achieve flight performance usually reserved for professional pilots, unlocking boundless potential for aerobatic flight evolution in uncrewed aerial vehicles.
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