A Hybrid Method for Online Safe Trajectory Generation in Quadrotor Flight

Yu Ding, Fubiao Zhang*, Defu Lin, Mingcheng Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we propose a safe and efficient online trajectory generation method for quadrotors. This algorithm combines the sample-based motion planning method with the time-constrained trajectory optimization method. Based on the linearized state-space model of the quadrotor, we use the ellipsoid heuristic to directly sample the map and consider reasonable energy loss and completion time under the motion constraints, and construct a smooth and feasible initial trajectory for obstacle avoidance through multiple iteration optimization strategies. By using B-spline trajectory optimization and convex hull property, we minimize the loss of smoothing term, collision term, and dynamic feasible term to ensure fast and safe trajectory generation online. The proposed method is verified by numerical experiments, and compared with the classical RRT* algorithm and Kinodynamic RRT* algorithm, it is proved that the proposed method can generate feasible quadrotor trajectories at a faster speed.

Original languageEnglish
Title of host publicationAdvances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control
EditorsLiang Yan, Haibin Duan, Yimin Deng, Liang Yan
PublisherSpringer Science and Business Media Deutschland GmbH
Pages2073-2084
Number of pages12
ISBN (Print)9789811966125
DOIs
Publication statusPublished - 2023
EventInternational Conference on Guidance, Navigation and Control, ICGNC 2022 - Harbin, China
Duration: 5 Aug 20227 Aug 2022

Publication series

NameLecture Notes in Electrical Engineering
Volume845 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Conference on Guidance, Navigation and Control, ICGNC 2022
Country/TerritoryChina
CityHarbin
Period5/08/227/08/22

Keywords

  • Obstacle avoidance
  • Trajectory planning
  • Unmanned aerial vehicle

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