JOURNAL ARTICLE
Unlocking aerobatic potential of quadcopters: Autonomous freestyle flight generation and execution.
Published In: Science Robotics, 2025, v. 10, n. 101. P. 1 1 of 3
Database: Applied Science & Technology Source Ultimate 2 of 3
Authored By: WANG, MINGYANG; Wang, Qianhao; Wang, Ze; Gao, Yuman; Wang, Jingping; Cui, Can; Li, Yuan; Ding, Ziming; Wang, Kaiwei; Xu, Chao; Gao, Fei 3 of 3
Abstract
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. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Science Robotics. 2025/04, Vol. 10, Issue 101, p1
- Document Type:Article
- Subject Area:Sports and Leisure
- Publication Date:2025
- ISSN:24709476
- DOI:10.1126/scirobotics.adp9905
- Accession Number:185162940
- Copyright Statement:Copyright of Science Robotics is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.