TY - GEN
T1 - Automated Landing of Quadrotors on an Unmanned Aerial Vehicle Carrier via Real-Time Trajectory Planning and Nonlinear Model Predictive Control
AU - Zhang, Chengchen
AU - Lam, Yat Long
AU - Ip, Chun Man Ben
AU - Huang, Hailong
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025/6
Y1 - 2025/6
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/105016151000
U2 - 10.1109/ICCA65672.2025.11129795
DO - 10.1109/ICCA65672.2025.11129795
M3 - Conference article published in proceeding or book
AN - SCOPUS:105016151000
T3 - IEEE International Conference on Control and Automation, ICCA
SP - 411
EP - 416
BT - 2025 IEEE 19th International Conference on Control and Automation, ICCA 2025
PB - IEEE Computer Society
T2 - 19th IEEE International Conference on Control and Automation, ICCA 2025
Y2 - 30 June 2025 through 3 July 2025
ER -