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arXiv · 2505.15010

Shape-Adaptive Planning and Control for a Deformable Quadrotor

Yuze Wu·Zhichao Han·Xuankang Wu·Yuan Zhou·Junjie Wang·Zheng Fang·Fei Gao
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Abstract

Drones have become essential in various applications, but conventional quadrotors face limitations in confined spaces and complex tasks. Deformable drones, which can adapt their shape in real-time, offer a promising solution to overcome these challenges, while also enhancing maneuverability and enabling novel tasks like object grasping. This paper presents a novel approach to autonomous motion planning and control for deformable quadrotors. We introduce a shape-adaptive trajectory planner that incorporates deformation dynamics into path generation, using a scalable kinodynamic A* search to handle deformation parameters in complex environments. The backend spatio-temporal optimization is capable of generating optimally smooth trajectories that incorporate shape deformation. Additionally, we propose an enhanced control strategy that compensates for external forces and torque disturbances, achieving a 37.3\% reduction in trajectory tracking error compared to our previous work. Our approach is validated through simulations and real-world experiments, demonstrating its effectiveness in narrow-gap traversal and multi-modal deformable tasks.

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Yuze Wu, Zhichao Han, Xuankang Wu, Yuan Zhou, Junjie Wang, Zheng Fang, Fei Gao. 2025-05-21. Shape-Adaptive Planning and Control for a Deformable Quadrotor. https://arxiv.org/abs/2505.15010

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