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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Main Authors: Chaojun Qin, Na Zhao, Qiuyu Wang, Yudong Luo, Yantao Shen
Format: Article
Language:English
Published: MDPI AG 2025-04-01
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.
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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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AT yudongluo minimumsnaptrajectoryplanningandaugmentedmpcformorphingquadrotornavigationinconfinedspaces
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