LOONG: Online Time-Optimal Autonomous Flight for MAVs in Cluttered Environments

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Authors: Xin Guan, Fangguo Zhao, Qianyi Wang, Chengcheng Zhao, Jiming Chen, Shuo Li
Cited by: 0

Abstract

Autonomous flight of micro air vehicles (MAVs) in unknown, cluttered environments remains challenging for time-critical missions due to conservative maneuvering strategies. This article presents an integrated planning and control framework for high-speed, time-optimal autonomous flight of MAVs in cluttered environments. In each replanning cycle (100 Hz), a time-optimal trajectory under polynomial presentation is generated as a reference, with the time-allocation process accelerated by imitation learning. Subsequently, a time-optimal model predictive contouring control (MPCC) incorporates safe flight corridor (SFC) constraints at variable horizon steps to enable aggressive yet safe maneuvering, while fully exploiting the MAV's dynamics. We validate the proposed framework extensively on a custom-built LiDAR-based MAV platform. Simulation results demonstrate superior aggressiveness compared to the state of the art, while real-world experiments achieve a peak speed of 18 m/s in a cluttered environment and succeed in 10 consecutive trials from diverse start points. The video is available at the following link: https://youtu.be/vexXXhv99oQ.

Fields of Study & Subjects

Robotic Path Planning Algorithms Aerospace Engineering and Control Systems Aerospace and Aviation Technology

Publication details

Journal / source
arXiv (Cornell University)
Publication date
12 January 2026
Document type
Preprint