Position Checking-Based Sampling Approach Combined with Attraction Point Local Optimization for Safe Flight of UAVs
Trading off the allocation of limited computational resources between front-end path generation and back-end trajectory optimization plays a key role in improving the efficiency of unmanned aerial vehicle (UAV) motion planning. In this paper, a sampling-based kinodynamic planning method that can red...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/7/2157 |
| _version_ | 1827286607098544128 |
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| author | Hai Zhu Baoquan Li Ruiyang Tong Haolin Yin Canlin Zhu |
| author_facet | Hai Zhu Baoquan Li Ruiyang Tong Haolin Yin Canlin Zhu |
| author_sort | Hai Zhu |
| collection | DOAJ |
| description | Trading off the allocation of limited computational resources between front-end path generation and back-end trajectory optimization plays a key role in improving the efficiency of unmanned aerial vehicle (UAV) motion planning. In this paper, a sampling-based kinodynamic planning method that can reduce the computational cost as well as the risks of UAV flight is proposed. Firstly, an initial trajectory connecting the start and end points without considering obstacles is generated. Then, a spherical space is constructed around the topological vertices of the environment, based on the intersections of the trajectory with the obstacles. Next, some unnecessary sampling points, as well as node rewiring, are discarded by the designed position-checking strategy to minimize the computational cost and reduce the risks of UAV flight. Finally, in order to make the planning framework adaptable to complex scenarios, the strategies for selecting different attraction points according to the environment are designed, which further ensures the safe flight of the UAV while improving the success rate of the front-end trajectory. Simulations and real-world experiment comparisons are conducted on a vision-based platform to verify the performance of the proposed method. |
| first_indexed | 2024-04-24T10:35:07Z |
| format | Article |
| id | doaj.art-e95d02ba290349bf931f1a7a8de2354e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-24T10:35:07Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e95d02ba290349bf931f1a7a8de2354e2024-04-12T13:26:21ZengMDPI AGSensors1424-82202024-03-01247215710.3390/s24072157Position Checking-Based Sampling Approach Combined with Attraction Point Local Optimization for Safe Flight of UAVsHai Zhu0Baoquan Li1Ruiyang Tong2Haolin Yin3Canlin Zhu4School of Control Science and Engineering, Tiangong University, Tianjin 300387, ChinaSchool of Control Science and Engineering, Tiangong University, Tianjin 300387, ChinaSchool of Control Science and Engineering, Tiangong University, Tianjin 300387, ChinaSchool of Control Science and Engineering, Tiangong University, Tianjin 300387, ChinaSchool of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, ChinaTrading off the allocation of limited computational resources between front-end path generation and back-end trajectory optimization plays a key role in improving the efficiency of unmanned aerial vehicle (UAV) motion planning. In this paper, a sampling-based kinodynamic planning method that can reduce the computational cost as well as the risks of UAV flight is proposed. Firstly, an initial trajectory connecting the start and end points without considering obstacles is generated. Then, a spherical space is constructed around the topological vertices of the environment, based on the intersections of the trajectory with the obstacles. Next, some unnecessary sampling points, as well as node rewiring, are discarded by the designed position-checking strategy to minimize the computational cost and reduce the risks of UAV flight. Finally, in order to make the planning framework adaptable to complex scenarios, the strategies for selecting different attraction points according to the environment are designed, which further ensures the safe flight of the UAV while improving the success rate of the front-end trajectory. Simulations and real-world experiment comparisons are conducted on a vision-based platform to verify the performance of the proposed method.https://www.mdpi.com/1424-8220/24/7/2157sampling-based plannerunmanned aerial vehiclemotion planning |
| spellingShingle | Hai Zhu Baoquan Li Ruiyang Tong Haolin Yin Canlin Zhu Position Checking-Based Sampling Approach Combined with Attraction Point Local Optimization for Safe Flight of UAVs Sensors sampling-based planner unmanned aerial vehicle motion planning |
| title | Position Checking-Based Sampling Approach Combined with Attraction Point Local Optimization for Safe Flight of UAVs |
| title_full | Position Checking-Based Sampling Approach Combined with Attraction Point Local Optimization for Safe Flight of UAVs |
| title_fullStr | Position Checking-Based Sampling Approach Combined with Attraction Point Local Optimization for Safe Flight of UAVs |
| title_full_unstemmed | Position Checking-Based Sampling Approach Combined with Attraction Point Local Optimization for Safe Flight of UAVs |
| title_short | Position Checking-Based Sampling Approach Combined with Attraction Point Local Optimization for Safe Flight of UAVs |
| title_sort | position checking based sampling approach combined with attraction point local optimization for safe flight of uavs |
| topic | sampling-based planner unmanned aerial vehicle motion planning |
| url | https://www.mdpi.com/1424-8220/24/7/2157 |
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