Robust and Efficient Trajectory Replanning Based on Guiding Path for Quadrotor Fast Autonomous Flight
Path planning is one of the key parts of unmanned aerial vehicle (UAV) fast autonomous flight in an unknown cluttered environment. However, real-time and stability remain a significant challenge in the field of path planning. To improve the robustness and efficiency of the path planning method in co...
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doaj-534b54d8456f41d39e74f84a163458872021-03-05T00:05:30ZengMDPI AGRemote Sensing2072-42922021-03-011397297210.3390/rs13050972Robust and Efficient Trajectory Replanning Based on Guiding Path for Quadrotor Fast Autonomous FlightYinghao Zhao0Li Yan1Yu Chen2Jicheng Dai3Yuxuan Liu4School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, ChinaSchool of Geodesy and Geomatics, Wuhan University, Wuhan 430079, ChinaSchool of Geodesy and Geomatics, Wuhan University, Wuhan 430079, ChinaSchool of Geodesy and Geomatics, Wuhan University, Wuhan 430079, ChinaInstitute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100036, ChinaPath planning is one of the key parts of unmanned aerial vehicle (UAV) fast autonomous flight in an unknown cluttered environment. However, real-time and stability remain a significant challenge in the field of path planning. To improve the robustness and efficiency of the path planning method in complex environments, this paper presents RETRBG, a robust and efficient trajectory replanning method based on the guiding path. Firstly, a safe guiding path is generated by using an improved A* and path pruning method, which is used to perceive the narrow space in its surrounding environment. Secondly, under the guidance of the path, a guided kinodynamic path searching method (GKPS) is devised to generate a safe, kinodynamically feasible and minimum-time initial path. Finally, an adaptive optimization function with two modes is proposed to improve the optimization quality in complex environments, which selects the optimization mode to optimize the smoothness and safety of the path according to the perception results of the guiding path. The experimental results demonstrate that the proposed method achieved good performance both in different obstacle densities and different resolutions. Compared with the other state-of-the-art methods, the quality and success rate of the planning result are significantly improved.https://www.mdpi.com/2072-4292/13/5/972UAVpath planningguiding pathkinodynamic path searchingadaptive optimization |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yinghao Zhao Li Yan Yu Chen Jicheng Dai Yuxuan Liu |
spellingShingle |
Yinghao Zhao Li Yan Yu Chen Jicheng Dai Yuxuan Liu Robust and Efficient Trajectory Replanning Based on Guiding Path for Quadrotor Fast Autonomous Flight Remote Sensing UAV path planning guiding path kinodynamic path searching adaptive optimization |
author_facet |
Yinghao Zhao Li Yan Yu Chen Jicheng Dai Yuxuan Liu |
author_sort |
Yinghao Zhao |
title |
Robust and Efficient Trajectory Replanning Based on Guiding Path for Quadrotor Fast Autonomous Flight |
title_short |
Robust and Efficient Trajectory Replanning Based on Guiding Path for Quadrotor Fast Autonomous Flight |
title_full |
Robust and Efficient Trajectory Replanning Based on Guiding Path for Quadrotor Fast Autonomous Flight |
title_fullStr |
Robust and Efficient Trajectory Replanning Based on Guiding Path for Quadrotor Fast Autonomous Flight |
title_full_unstemmed |
Robust and Efficient Trajectory Replanning Based on Guiding Path for Quadrotor Fast Autonomous Flight |
title_sort |
robust and efficient trajectory replanning based on guiding path for quadrotor fast autonomous flight |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2021-03-01 |
description |
Path planning is one of the key parts of unmanned aerial vehicle (UAV) fast autonomous flight in an unknown cluttered environment. However, real-time and stability remain a significant challenge in the field of path planning. To improve the robustness and efficiency of the path planning method in complex environments, this paper presents RETRBG, a robust and efficient trajectory replanning method based on the guiding path. Firstly, a safe guiding path is generated by using an improved A* and path pruning method, which is used to perceive the narrow space in its surrounding environment. Secondly, under the guidance of the path, a guided kinodynamic path searching method (GKPS) is devised to generate a safe, kinodynamically feasible and minimum-time initial path. Finally, an adaptive optimization function with two modes is proposed to improve the optimization quality in complex environments, which selects the optimization mode to optimize the smoothness and safety of the path according to the perception results of the guiding path. The experimental results demonstrate that the proposed method achieved good performance both in different obstacle densities and different resolutions. Compared with the other state-of-the-art methods, the quality and success rate of the planning result are significantly improved. |
topic |
UAV path planning guiding path kinodynamic path searching adaptive optimization |
url |
https://www.mdpi.com/2072-4292/13/5/972 |
work_keys_str_mv |
AT yinghaozhao robustandefficienttrajectoryreplanningbasedonguidingpathforquadrotorfastautonomousflight AT liyan robustandefficienttrajectoryreplanningbasedonguidingpathforquadrotorfastautonomousflight AT yuchen robustandefficienttrajectoryreplanningbasedonguidingpathforquadrotorfastautonomousflight AT jichengdai robustandefficienttrajectoryreplanningbasedonguidingpathforquadrotorfastautonomousflight AT yuxuanliu robustandefficienttrajectoryreplanningbasedonguidingpathforquadrotorfastautonomousflight |
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1724231345615405056 |