Minimum Snap Trajectory Planning and Augmented MPC for Morphing Quadrotor Navigation in Confined Spaces
Existing studies rarely investigate the dynamic morphology factor on motion planning and control, which is crucial for morphing quadrotors to achieve autonomous flight. Therefore, this paper studies the collaborative optimization of trajectory generation and flight control for the morphing quadrotor...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/9/4/304 |
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| author | Chaojun Qin Na Zhao Qiuyu Wang Yudong Luo Yantao Shen |
| author_facet | Chaojun Qin Na Zhao Qiuyu Wang Yudong Luo Yantao Shen |
| author_sort | Chaojun Qin |
| collection | DOAJ |
| description | Existing studies rarely investigate the dynamic morphology factor on motion planning and control, which is crucial for morphing quadrotors to achieve autonomous flight. Therefore, this paper studies the collaborative optimization of trajectory generation and flight control for the morphing quadrotor with real-time adjustable arms. In the motion planning layer, an objective function that combines position and morphology is constructed by embedding variable arm length as a decision variable into the conventional minimum snap trajectory generation framework. The generated trajectory not only satisfies the speed and acceleration constraints, but also smoothly passes through the narrow spaces that are difficult for traditional quadrotors to traverse. In the control layer, a constrained augmented model predictive control based on the dynamics of the morphing quadrotors is proposed to follow the generated trajectory with an embedded integrator, which is added by exploiting the differential flat variables to improve the tracking performance. In the numerical studies, a scenario with a corridor was considered to demonstrate the effectiveness of the proposed control strategy to achieve optimal trajectory under multiple constraints. |
| format | Article |
| id | doaj-art-53e3988cf36b4d679d042e1b1d31ab35 |
| institution | OA Journals |
| issn | 2504-446X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-53e3988cf36b4d679d042e1b1d31ab352025-08-20T02:17:20ZengMDPI AGDrones2504-446X2025-04-019430410.3390/drones9040304Minimum Snap Trajectory Planning and Augmented MPC for Morphing Quadrotor Navigation in Confined SpacesChaojun Qin0Na Zhao1Qiuyu Wang2Yudong Luo3Yantao Shen4Department of Computer Science and Technology, Dalian Maritime University, Dalian 116026, ChinaDepartment of Computer Science and Technology, Dalian Maritime University, Dalian 116026, ChinaDepartment of Computer Science and Technology, Dalian Maritime University, Dalian 116026, ChinaDepartment of Computer Science and Technology, Dalian Maritime University, Dalian 116026, ChinaDepartment of Electrical and Biomedical Engineering, University of Nevada, Reno, NV 89557, USAExisting studies rarely investigate the dynamic morphology factor on motion planning and control, which is crucial for morphing quadrotors to achieve autonomous flight. Therefore, this paper studies the collaborative optimization of trajectory generation and flight control for the morphing quadrotor with real-time adjustable arms. In the motion planning layer, an objective function that combines position and morphology is constructed by embedding variable arm length as a decision variable into the conventional minimum snap trajectory generation framework. The generated trajectory not only satisfies the speed and acceleration constraints, but also smoothly passes through the narrow spaces that are difficult for traditional quadrotors to traverse. In the control layer, a constrained augmented model predictive control based on the dynamics of the morphing quadrotors is proposed to follow the generated trajectory with an embedded integrator, which is added by exploiting the differential flat variables to improve the tracking performance. In the numerical studies, a scenario with a corridor was considered to demonstrate the effectiveness of the proposed control strategy to achieve optimal trajectory under multiple constraints.https://www.mdpi.com/2504-446X/9/4/304morphing quadrotortrajectory generationmodel predictive control |
| spellingShingle | Chaojun Qin Na Zhao Qiuyu Wang Yudong Luo Yantao Shen Minimum Snap Trajectory Planning and Augmented MPC for Morphing Quadrotor Navigation in Confined Spaces Drones morphing quadrotor trajectory generation model predictive control |
| title | Minimum Snap Trajectory Planning and Augmented MPC for Morphing Quadrotor Navigation in Confined Spaces |
| title_full | Minimum Snap Trajectory Planning and Augmented MPC for Morphing Quadrotor Navigation in Confined Spaces |
| title_fullStr | Minimum Snap Trajectory Planning and Augmented MPC for Morphing Quadrotor Navigation in Confined Spaces |
| title_full_unstemmed | Minimum Snap Trajectory Planning and Augmented MPC for Morphing Quadrotor Navigation in Confined Spaces |
| title_short | Minimum Snap Trajectory Planning and Augmented MPC for Morphing Quadrotor Navigation in Confined Spaces |
| title_sort | minimum snap trajectory planning and augmented mpc for morphing quadrotor navigation in confined spaces |
| topic | morphing quadrotor trajectory generation model predictive control |
| url | https://www.mdpi.com/2504-446X/9/4/304 |
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