Journal of Jilin University(Engineering and Technology Edition) ›› 2023, Vol. 53 ›› Issue (9): 2732-2740.doi: 10.13229/j.cnki.jdxbgxb.20211187

Previous Articles    

Dynamic obstacle avoidance strategy for flapping⁃wing micro air vehicles

Hao ZHENG1(),Li-jun YU1,Peng-peng ZHI1,2,Zhong-lai WANG1,2()   

  1. 1.School of Mechanical and Electrical Engineering，University of Electronic Science and Technology of China，Chengdu 611731，China
    2.Yangtze Delta Region Institute （Huzhou），University of Electronic Science and Technology of China，Huzhou 313099，China
  • Received:2021-11-14 Online:2023-09-01 Published:2023-10-09
  • Contact: Zhong-lai WANG E-mail:201821040136@std.uestc.edu.cn;wzhonglai@uestc.edu.cn

RICH HTML

 5   

PDF (PC)

273

Abstract:

Aiming at the dynamic obstacle avoidance problem during the flying process of the Flapping-wing Micro Air Vehicle （FWMAV）， a novel obstacle avoidance scheduling strategy integrating the global path planning and the locally dynamic path planning is proposed in this paper. The static comprehensive cost model is first built by considering both the performance constraints of the FWMAV and its threat constraints during the flight environment. Based on the static cost model， a time-varying collision constraint between the FWMAV and dynamic obstacles is defined and then the dynamic comprehensive cost model for the local obstacle avoidance is established. The improved ant colony algorithm is proposed for the obstacle avoidance scheduling strategy optimization. The results show that the proposed method can effectively handle the dynamic obstacle avoidance scheduling problem of the FWMAV under the known map and improve the dynamic obstacle avoidance scheduling strategy under the dynamic obstacles； meanwhile the improved ant colony algorithm can promote the efficiency of the dynamic path optimization to ensure the real-time requirement of the obstacle avoidance control of the FWMAV.

Key words: flapping-wing micro air vehicle, cost model, obstacle avoidance strategy, dynamic path planning

CLC Number: 

  • V276

Fig.1

Description of the flight trajectory"

Fig.2

Schematic diagram of the trajectories of the FWMAV and the obstacles"

Fig.3

Collision threshold ε selection"

Fig.4

Flow chart of the path planning algorithm for FWMAV"

Table 1

Performance parameters of the FWMAV prototype"

参数取值
翼展/cm26
机身重量/g30
额外负载/g20
飞行速度/（m·s-1）2
最远飞行距离/km2
最小转弯半径/m0.41
飞行高度范围/m［0，50］

Fig.5

Digital map of three-dimensional environment space"

Fig.6

Results of the global obstacle avoidance path planning for FWMAV"

Fig.7

Correlation between the iteration time and the fitness value"

Table 2

Path planning result comparison between the improved ACO and the conventional ACO algorithm"

传统ACO改进ACO算法改进提升
Len/mHgt/mTim/sRate/%Len/mHgt/mTim/sRate/%Len/mTim/sRate/%
162612723.6542.71587856.8061.33916.8518.6

Fig.8

Local dynamic path planning results of FWMAV"

1 Phan H V, Aurecianus S, Au T K L, et al. Towards long-endurance flight of an insect-inspired, tailless, two-winged, flapping-wing flying robot[J]. IEEE Robotics and Automation Letters, 2020, 5(4): 5059-5066.
2 Zhi P, Xu Y, Chen B. Time-dependent reliability analysis of the motor hanger for EMU based on stochastic process[J]. International Journal of Structural Integrity, 2020, 11(3): 453-469.
3 Li Y H, Sheng Z, Zhi P, et al. Multi-objective optimization design of anti-rolling torsion bar based on modified NSGA-III algorithm[J]. International Journal of Structural Integrity, 2021, 12(1): 17-30.
4 霍凤财, 迟金, 黄梓健, 等. 移动机器人路径规划算法综述[J]. 吉林大学学报: 工学版, 2018, 36(6): 639-647.
Huo Feng-cai, Chi Jin, Huang Zi-jian, et al. Review of path planning for mobile robots[J]. Journal of Jilin University (Engineering and Technology Edition), 2018, 36(6): 639-647.
5 Triharminto H H, Prabuwono A S, Adji T B, et al. UAV dynamic path planning for intercepting of a moving target: a review[J]. Communications in Computer & Information Science, 2013, 376: 206-219.
6 程谦, 高嵩, 曹凯, 等. 基于PRM优化算法的移动机器人路径规划[J]. 计算机应用与软件, 2020, 37(12): 254-259.
Cheng qian, Gao song, Cao kai, et al. Path planning of mobile robot based on PRM optimization algorithm[J]. Computer Applications and Software, 2020, 37(12): 254-259.
7 Kong X D, Pan B, Cherkashin E, et al. Multi-constraint UAV fast path planning based on improved A* algorithm[J]. Journal of Physics: Conference Series, 2020, 1624(4): No.042009.
8 林韩熙, 向丹, 欧阳剑, 等. 移动机器人路径规划算法的研究综述[J]. 计算机工程与应用, 2021, 57(18): 38-48.
Lin Han-xi, Xiang Dan, Ouyang Jian, et al. Review of path planning algorithms for mobile robots[J]. Computer Engineering and Applications, 2021, 57(18): 38-48.
9 戴健, 许菲, 陈琪锋. 多无人机协同搜索区域划分与路径规划[J]. 航空学报, 2020, 41(): 149-156.
Dai Jian, Xu Fei, Chen Qi-feng. Multi-UAV cooperative search on region division and path planning[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(Sup.1): 149-156.
10 李波, 杨志鹏, 贾卓然, 等. 一种无监督学习型神经网络的无人机全区域侦察路径规划[J]. 西北工业大学学报, 2021, 39(1): 77-84.
Li Bo, Yang Zhi-peng, Jia Zhuo-ran. An unsupervised learning neural network for planning UAV full-area reconnaissance path[J]. Journal of Northwestern Polytechnical University, 2021, 39(1): 77-84.
11 王巍, 梁桥. 基于单目视觉和惯性测量的飞行器自定位研究[J]. 吉林大学学报: 工学版, 2016, 34(6): 774-780.
Wang Wei, Liang Qiao. Research of ego-positioning for micro air vehicles based on monocular vision and inertial measurement[J]. Journal of Jilin University (Engineering and Technology Edition), 2016, 34(6): 774-780.
12 王晓东, 张永强, 薛红. 基于改进蚁群算法对VRP线路优化[J]. 吉林大学学报: 工学版, 2017, 35(2): 198-203.
Wang Xiao-dong, Zhang Yong-qiang, Xue Hong. Improved ant colony algorithm for VRP[J]. Journal of Jilin University (Engineering and Technology Edition), 2017, 35(2): 198-203.
13 Ho H W, Wagter C D, Remes B D W, et al. Optical-flow based self-supervised learning of obstacle appearance applied to MAV landing[J]. Robotics and Autonomous Systems, 2018, 100: 78-94.
14 Tijmons S, Croon D G C H E, Remes B D W, et al. Obstacle avoidance strategy using onboard stereo vision on a flapping wing MAV[J]. IEEE Transactions on Robotics, 2017, 33(4): 858-874.
15 Tu Z, Fei F, Zhang J, et al. Acting is seeing: navigating tight space using flapping wings[C]∥2019 International Conference on Robotics and Automation, Montreal, Canada, 2019: 95-101.
16 余立均. 仿生扑翼微型飞行器路径规划研究[D]. 成都: 电子科技大学航空学院, 2021.
Yu Li-jun. Study on path planning of bio-inspired flapping-wing micro aerial vehicles[D]. Chengdu: College of Aeronautics, University of Electronic Science and Technology of China, 2021.
[1] Yu-quan YAO,Jian-gang YANG,Jie GAO,Liang SONG. Optimal design on recycled hot⁃mix asphalt mixture based on performance⁃cost model [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(3): 585-595.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] LI Shoutao, LI Yuanchun. Autonomous Mobile Robot Control Algorithm Based on Hierarchical Fuzzy Behaviors in Unknown Environments[J]. 吉林大学学报(工学版), 2005, 35(04): 391 -397 .
[2] Li Hong-ying; Shi Wei-guang;Gan Shu-cai. Electromagnetic properties and microwave absorbing property
of Z type hexaferrite Ba3-xLaxCo2Fe24O41[J]. 吉林大学学报(工学版), 2006, 36(06): 856 -0860 .
[3] Li Yue-ying，Liu Yong-bing，Chen Hua . Surface hardening and tribological properties of a cam materials[J]. 吉林大学学报(工学版), 2007, 37(05): 1064 -1068 .
[4] Zhang He-sheng, Zhang Yi, Wen Hui-min, Hu Dong-cheng . Estimation approaches of average link travel time using GPS data[J]. 吉林大学学报(工学版), 2007, 37(03): 533 -0537 .
[5] Yang Shu-kai, Song Chuan-xue, An Xiao-juan, Cai Zhang-lin . Analyzing effects of suspension bushing elasticity
on vehicle yaw response character with virtual prototype method[J]. 吉林大学学报(工学版), 2007, 37(05): 994 -0999 .
[6] . [J]. 吉林大学学报(工学版), 2007, 37(06): 1284 -1287 .
[7] Liu Han-bing, Jiao Yu-ling, Liang Chun-yu,Qin Wei-jun . Effect of shape function on computing precision in meshless methods[J]. 吉林大学学报(工学版), 2007, 37(03): 715 -0720 .
[8] Yang Qing-fang, Chen Lin . Division approach of traffic control work zone[J]. 吉林大学学报(工学版), 2006, 36(增刊2): 139 -142 .
[9] Qu Zhao-wei，Chen Hong-yan，Li Zhi-hui，Hu Hong-yu，Wei Wei . 2D view reconstruction method based on single calibration pattern
[J]. 吉林大学学报(工学版), 2007, 37(05): 1159 -1163 .
[10] Tang Xin-xing，Zhao Ding-xuan，Huang Hai-dong，Ai Xue-zhong,Feng Shi-zhu . Modified stereo vision calibration method for construction robot
[J]. 吉林大学学报(工学版), 2007, 37(02): 391 -0395 .
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd