Automated Landing of Quadrotors on an Unmanned Aerial Vehicle Carrier via Real-Time Trajectory Planning and Nonlinear Model Predictive Control
Chengchen Zhang, Yat Long Lam, Chun Man Ben Ip, Hailong Huang · 2025
This paper explores the deployment of a mobile unmanned aerial vehicle carrier (UAVC) system, facilitating the landing of unmanned aerial vehicles (UAVs) on a moving platform, thereby enhancing their operational range and flexibility. The primary contributions of this study include the development of an advanced trajectory planner that integrates Jump Point Search (JPS) with gradient-based trajectory optimization to ensure efficient and collision-free navigation in complex environments. Furthermore, a Nonlinear Model Predictive Control (NMPC) framework is employed to achieve precise and stable trajectory tracking for both the UAV and UAVC. Extensive simulations conducted in Gazebo validate the efficacy of the proposed approach, demonstrating successful landings on a UAV carrier under a complex environment.