@inproceedings{8d99c15a78b24a49bd8c6b6a167d7807,
title = "Model Predictive Contour Control–Based Autonomous Landing of a Quadrotor on a Moving Ground Vehicle",
abstract = "This study presents a model predictive contour control (MPCC)–based landing guidance framework for an unmanned aerial vehicle (UAV) performing autonomous landing on a moving unmanned ground vehicle (UGV). The proposed approach relies solely on dynamic state feedback, incorporating sensor noise considerations, and conducts real-time optimization to minimize both contouring and lag errors relative to the moving platform. By integrating prediction and correction within a unified MPCC formulation, the method achieves smooth and stable descent. Simulation results under dynamically varying and noisy motion conditions demonstrate that the proposed framework ensures precise, smooth, and disturbance-tolerant landing performance.",
keywords = "autonomous landing, disturbance tolerance, MPCC, UAV–UGV cooperation",
author = "Wenjing Ren and Xin Dong and Jinwu Xiang and Daochun Li and Yangjie Cui and Zhan Tu",
note = "Publisher Copyright: {\textcopyright}2025 IEEE.; 7th International Conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2025 ; Conference date: 14-11-2025 Through 16-11-2025",
year = "2025",
doi = "10.1109/RICAI68060.2025.11385214",
language = "英语",
series = "2025 7th International Conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "259--264",
booktitle = "2025 7th International Conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2025",
address = "美国",
}