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Journal of Projectiles, Rockets, Missiles and Guidance >

2022 , Vol. 42 >Issue 5: 92 - 97

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2022.05.017

Online Avoidance Path Planning Method for Quadrotor

  • ZHAO Wenjiao 1 ,
  • GAN Xusheng 2
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  • 1 College of Traffic Engineering, Shanxi Vocational University of Engineering and Technology, Jinzhong 030619, Shanxi, China
  • 2 Air Traffic Control and Navigation College,Air Force Engineering University,Xi’an 710051,China

Received date: 2022-03-23

  Online published: 2025-01-16

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Abstract

In order to meet the real-time obstacle avoidance requirements of quadrotor in urban, mountainous and dense forest environments, an online flight path planning method for quadrotor is proposed. On the basis of analyzing the spatial motion of the quadrotor, the segmented polynomial is used to model the flight path of the quadrotor. The distance cost, collision cost, speed and acceleration penalty terms are introduced. The initial track is attracted to the free space through geometric guidance to form an avoidance track. The smoothness and dynamic feasibility of the avoidance track are optimized by combining the track smoothing estimation, thus, the capability of online avoidance and flight path replanning of quadrotor can be realized. Finally in a complex environment model, the simulation results are compared in terms of the computation time, computing complexity and the success rate. The simulation results show that the method has the characterristics of high computing efficiency, good smoothness and high success rate. It can avoid collision threat automatically in unknown environment and fast flight, and is more suitable for online avoidance route planning of quadrotor.

Key words： quadrotor; online avoidance; path planning; piecewise polynomial

Cite this article

ZHAO Wenjiao , GAN Xusheng . Online Avoidance Path Planning Method for Quadrotor[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2022 , 42(5) : 92 -97 . DOI: 10.15892/j.cnki.djzdxb.2022.05.017

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References

Publishing order | Descend order by publishing year | Descend order by cited within
[1]
黄雨杨, 郝峰. 基于文化-禁忌搜索算法的巡飞弹航迹规划[J]. 弹箭与制导学报, 2020, 40(2):63-66.

[2]
姜琛, 李涛, 赵宏生. 基于双观测器的四旋翼无人机姿态控制[J]. 南京信息工程大学学报(自然科学版), 2022, 14(4):502-508.

[3]
陈韶千, 董国才, 唐同斌, 等. 基于概略图的航迹优化的改进A*算法研究[J]. 弹箭与制导学报, 2019, 39(1):131-134.

[4]
周哲媚, 陈璞. 基于改进自适应遗传算法的无人机三维航迹规划[EB/OL].(2020-12-20)[2022-03-13]. http://kns.cnki.net/kcms/detail/61.1234.TJ.20201202.1523.002.html.

[5]
成浩浩, 杨森, 齐晓慧. 面向城市环境的四旋翼无人机在线避障航迹规划方法[J]. 计算机科学, 2019, 46(4):241-246.

[6]
王辰. 多旋翼无人机在军事后勤领域中的应用及发展趋势分析[J]. 飞航导弹, 2021(8):56-60.

[7]
卢艳军, 李月茹. 基于改进人工势场法的四旋翼飞行器航迹规划[J]. 火力与指挥控制, 2018, 43(11):119-122.

[8]
USENKO V, STUMBERG L V, PANGERCIC A, et al. Realtime trajectory replanning for mavs using uniform b-splines and a 3d circular buffer[C]// IEEE. Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems. New York: IEEE, 2017: 215-222.

[9]
GAO F, WANG L, ZHOU B, et al. Teach-repeat-replan: A complete and robust system for aggressive flight in complex environments[J]. IEEE Transactions on Robotics, 2020, 36(5): 1526-1545.

[10]
张宏鹏, 黄长强, 唐上钦, 等. 基于卷积神经网络的无人作战飞机飞行轨迹实时预测[J]. 兵工学报, 2020, 41(9):1894-1903.

DOI

[11]
陈都, 孟秀云. 基于改进ARA*算法的无人机在线航迹规划[J]. 飞行力学, 2021, 39(1):60-65.

[12]
王振, 刘苹妮, 马国亮. 变桨距四旋翼无人飞行器航迹跟踪控制[J]. 火力与指挥控制, 2020, 45(8):103-108.

[13]
张丹萌, 甄子洋, 陈棪. 基于改进RRT-Connect的协同航迹规划[J]. 电光与控制, 2021, 28(9):25-29.

[14]
赵红超, 周洪庆, 王书湖. 无人机三维航迹规划的量子粒子群优化算法[J]. 航天控制, 2021, 39(1):40-45.

[15]
ZHOU W F, LI B Y, SUN J X, et al. Position control of a tailsitter UAV using successivel inearization based model predictive control[J]. Control Engineering Practice, 2019, 91: 1-13.

[16]
王成, 杨杰, 姚辉, 等. 四旋翼无人机飞行控制算法综述[J]. 电光与控制, 2018, 25(12):53-58.

[17]
高俊山, 段立勇, 邓立为. 四旋翼无人机抗干扰轨迹跟踪控制[J]. 控制与决策, 2021, 36(2):379-386.

[18]
MELLINGER D, KUMAR V. Minimum snap trajectory generation and control for quadrotors[C]// IEEE. Proceedings of the 2011 IEEE International Conference on Robotics and Automation, 2011: 2520-2525.

[19]
NIEUWSTADT M J V, MURRAY R M. Real-time trajectory generation for differentially flat systems[J]. International Journal of Robust and Nonlinear Control, 1998, 8(11): 995-1020.

[20]
BURRI M, OLEYNIKOVA H, ACHTELIK M, et al. Real-time visualinertial mapping, relocalization and planning onboard mavs in unknown environments[C]// IEEE. Proceedings of the 2015 IEEE/RSJ International Conference Intelligent Robots and Systems. New York: IEEE, 2015: 1872-1878.

[21]
SCHULMAN J, DUAN Y, HO J, et al. Motion planning with sequential convex optimization and convex collision checking[J]. The International Journal of Robotics Research, 2014, 9(33): 1251-1270.

[22]
ZHOU B Y, GAO F, WANG L Q, et al. Robust and efficient quadrotor trajectory generation for fast autonomous flight[J]. IEEE Robotics and Automation Letters, 2019, 4(4): 3529-3536.

[23]
RICHTER C, BRY A, ROY N. Polynomial trajectory planning for aggressive quadrotor flight in dense indoor environments[C]// ISRR. Proceedings of the International Conference on Robotics and Automation. Michigan: CMES Inc., 2013: 649-666.

[24]
李文广, 胡永江, 孙世宇, 等. 无人机任务规划约束空间建模[J]. 现代防御技术, 2019, 47(4):7-13.

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