Shape-Adaptive Planning and Control for a Deformable Quadrotor
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.
Cite
@article{arxiv.2505.15010,
title = {Shape-Adaptive Planning and Control for a Deformable Quadrotor},
author = {Yuze Wu and Zhichao Han and Xuankang Wu and Yuan Zhou and Junjie Wang and Zheng Fang and Fei Gao},
journal= {arXiv preprint arXiv:2505.15010},
year = {2025}
}