Safety-Critical Online Quadrotor Trajectory Planner for Agile Flights in Unknown Environments
Jiazhe Yuan, Dongcheng Cao, Jiahao Mei, Jiming Chen, Shuo Li
Abstract
Autonomous high-speed flight in unknown, clut-tered environments is essential for a variety of quadrotor applications, such as inspection, search, and rescue. In this study, we propose a novel trajectory planner designed to achieve efficient, high-speed, collision-free flights in such environments. The proposed approach begins by generating a safe flight corridor based on the path found by Lazy Theta*, representing the safe regions with polytopic sets. These sets are then used to define discrete-time control barrier function (DCBF), ensuring the quadrotor stays within safe bounds during flight. By selecting a single waypoint ahead of the quadrotor on the path as the next waypoint, the trajectory is optimized by considering both the total flight time and safety constraints. Extensive simulations and real-world experiments have confirmed our method's feasibility, demonstrating its capability for high-speed performance and reliable obstacle avoidance. [video<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup><sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup>https://www.youtube.com/playlist?list=PLJFduoH7QICOhcIX3JFsZwB4IgS4_-sPt]
BibTeX
@inproceedings{icra2025_safetycriticalon,
title = {Safety-Critical Online Quadrotor Trajectory Planner for Agile Flights in Unknown Environments},
author = {Jiazhe Yuan and Dongcheng Cao and Jiahao Mei and Jiming Chen and Shuo Li},
booktitle = {ICRA 2025},
year = {2025}
}