{"title":"Unlocking aerobatic potential of quadcopters: Autonomous freestyle flight generation and execution","authors":"Mingyang Wang, Qianhao Wang, Ze Wang, Yuman Gao, Jingping Wang, Can Cui, Yuan Li, Ziming Ding, Kaiwei Wang, Chao Xu, Fei Gao","doi":"10.1126/scirobotics.adp9905","DOIUrl":null,"url":null,"abstract":"<div >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.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"10 101","pages":""},"PeriodicalIF":26.1000,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science Robotics","FirstCategoryId":"94","ListUrlMain":"https://www.science.org/doi/10.1126/scirobotics.adp9905","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Science Robotics publishes original, peer-reviewed, science- or engineering-based research articles that advance the field of robotics. The journal also features editor-commissioned Reviews. An international team of academic editors holds Science Robotics articles to the same high-quality standard that is the hallmark of the Science family of journals.
Sub-topics include: actuators, advanced materials, artificial Intelligence, autonomous vehicles, bio-inspired design, exoskeletons, fabrication, field robotics, human-robot interaction, humanoids, industrial robotics, kinematics, machine learning, material science, medical technology, motion planning and control, micro- and nano-robotics, multi-robot control, sensors, service robotics, social and ethical issues, soft robotics, and space, planetary and undersea exploration.