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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.03346 |
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| _version_ | 1866910859563892736 |
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| author | Wang, Yiming Ma, Jianbin Wu, Junda Li, Huizhe Zhou, Zhexuan Gong, Youmin Mei, Jie Ma, Guangfu |
| author_facet | Wang, Yiming Ma, Jianbin Wu, Junda Li, Huizhe Zhou, Zhexuan Gong, Youmin Mei, Jie Ma, Guangfu |
| contents | For quadrotors, achieving safe and autonomous flight in complex environments with wind disturbances and dynamic obstacles still faces significant challenges. Most existing methods address wind disturbances in either trajectory planning or control, which may lead to hazardous situations during flight. The emergence of dynamic obstacles would further worsen the situation. Therefore, we propose an efficient and reliable framework for quadrotors that incorporates wind disturbance estimations during both the planning and control phases via a generalized proportional integral observer. First, we develop a real-time adaptive spatial-temporal trajectory planner that utilizes Hamilton-Jacobi (HJ) reachability analysis for error dynamics resulting from wind disturbances. By considering the forward reachability sets propagation on an Euclidean Signed Distance Field (ESDF) map, safety is guaranteed. Additionally, a Nonlinear Model Predictive Control (NMPC) controller considering wind disturbance compensation is implemented for robust trajectory tracking. Simulation and real-world experiments verify the effectiveness of our framework. The video and supplementary material will be available at https://github.com/Ma29-HIT/SEAL/. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_03346 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SEAL: Safety Enhanced Trajectory Planning and Control Framework for Quadrotor Flight in Complex Environments Wang, Yiming Ma, Jianbin Wu, Junda Li, Huizhe Zhou, Zhexuan Gong, Youmin Mei, Jie Ma, Guangfu Systems and Control For quadrotors, achieving safe and autonomous flight in complex environments with wind disturbances and dynamic obstacles still faces significant challenges. Most existing methods address wind disturbances in either trajectory planning or control, which may lead to hazardous situations during flight. The emergence of dynamic obstacles would further worsen the situation. Therefore, we propose an efficient and reliable framework for quadrotors that incorporates wind disturbance estimations during both the planning and control phases via a generalized proportional integral observer. First, we develop a real-time adaptive spatial-temporal trajectory planner that utilizes Hamilton-Jacobi (HJ) reachability analysis for error dynamics resulting from wind disturbances. By considering the forward reachability sets propagation on an Euclidean Signed Distance Field (ESDF) map, safety is guaranteed. Additionally, a Nonlinear Model Predictive Control (NMPC) controller considering wind disturbance compensation is implemented for robust trajectory tracking. Simulation and real-world experiments verify the effectiveness of our framework. The video and supplementary material will be available at https://github.com/Ma29-HIT/SEAL/. |
| title | SEAL: Safety Enhanced Trajectory Planning and Control Framework for Quadrotor Flight in Complex Environments |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2503.03346 |