西南交通大学学报2023，Vol.58Issue(6)：1267-1276,10.DOI:10.3969/j.issn.0258-2724.20220262
基于极大化思想的无人机安全避障域识别算法
Recognition Algorithm of Safe Obstacle Avoidance Domain for UAVs Based on Maximization Idea
摘要
Abstract
In order to improve the accuracy and real-time performance of obstacle avoidance for quad-rotor helicopters,an obstacle avoidance algorithm combining the Lucas-Kanade(LK)optical flow method and maximization idea was proposed.Firstly,the video stream collected by the quad-rotor helicopter was preprocessed to obtain the image frame.Secondly,corner points whose optical flow was less than the threshold value in the image frame were eliminated by the LK optical flow method,and corner points were grouped by a clustering algorithm based on corner point distance.In addition,the outsourcing contour of each group of corner points was calculated.Then,the safe obstacle avoidance domain algorithm based on the maximization idea was used to calculate the optimal passing domain,and the deviation data were obtained according to the obstacle avoidance domain.Finally,the deviation data were input to the proportional and differential(PD)controller to obtain the control information,and the control command was sent to make the quad-rotor helicopter adjust the flight attitude in time to complete the obstacle avoidance flight.Experiments on the Tello quad-rotor helicopter in different scenes show that the proposed algorithm takes an average of 0.17 seconds to calculate the optimal safe obstacle avoidance domain for each frame of the image,which meets the real-time requirements of unmanned aerial vehicle(UAV)obstacle avoidance and solves the problem of identifying obstacle domains and calculating safe obstacle avoidance domain.关键词
极大化思想/安全避障域/四轴飞行器Key words
maximization idea/safe obstacle avoidance domain/quad-rotor helicopter分类
信息技术与安全科学引用本文复制引用
王家亮,董楷,顾兆军,陈辉,韩强..基于极大化思想的无人机安全避障域识别算法[J].西南交通大学学报,2023,58(6):1267-1276,10.基金项目
天津市教委科研计划(2020KJ026) （2020KJ026）
