东北大学学报(自然科学版) ›› 2024, Vol. 45 ›› Issue (1): 1-9.DOI: 10.12068/j.issn.1005-3026.2024.01.001

• 信息与控制 •    下一篇

基于多传感器融合的无人舰载机舰面定位研究

侯鹏帅1, 周大鹏2, 杨大鹏2, 陈杰1   

  1. 1.东北大学 机械工程与自动化学院,辽宁 沈阳 110819
    2.中国航空工业集团有限公司 沈阳飞机设计研究所,辽宁 沈阳 110035
  • 收稿日期:2022-07-21 出版日期:2024-01-15 发布日期:2024-04-02
  • 作者简介:侯鹏帅(1998-),男,山西忻州人,东北大学博士研究生
    陈 杰(1988-),男,山西五台人,东北大学副教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(52175004);中央高校基本科研业务费专项资金资助项目(N2203013)

Research on Positioning of Unmanned Carrier-Based Aircraft Based on Multi-sensor Fusion in Ship’s Surface Environment

Peng-shuai HOU1, Da-peng ZHOU2, Da-peng YANG2, Jie CHEN1   

  1. 1.School of Mechanical Engineering & Automation, Northeastern University, Shenyang 110819, China
    2.Shenyang Aircraft Design & Research Institute, Aviation Industry Corporation of China, Ltd. , Shenyang 110035, China. Corresponding author: CHEN Jie, E-mail: chenjie@me. neu. edu. cn
  • Received:2022-07-21 Online:2024-01-15 Published:2024-04-02

摘要:

无人舰载机在航母舰面的自主定位是实现自主转运、提高驶入/驶出效率的重要前提.其中,如何依靠机载传感设备实现GPS拒止环境下的舰载机自主舰面定位是亟待解决的关键技术.为此,提出了一种基于视觉和激光雷达融合的无人舰载机舰面自主定位算法.该算法通过结合手眼标定和互信息标定方法进行多传感器在线标定,使无人舰载机在面对风浪及航母运行等情况下机身摇晃导致传感器外参标定结果变化后仍能保持稳定运行;引入因子图用于无人舰载机的多传感器位姿联合优化并基于自主转运过程中的运动模型建立了简单高效的传感器失效标准,从而有效地融合了激光雷达和视觉定位结果,使该算法在单个传感器失效的情况下依然可以进行精确的自主定位;最后建立了基于多传感器的舰载机舰面仿真系统对本文算法进行验证,实验结果表明,本文算法在单个传感器失效的情况下定位误差仍维持在0.2 m以内,满足实际应用要求.

关键词: 无人舰载机, 多传感器融合, 自主定位, 在线标定, 舰面仿真

Abstract:

The autonomous positioning of unmanned carrier-based aircraft on the aircraft carrier is an important prerequisite for realizing autonomous transfer and improving the efficiency of entry/exit. Among them, how to rely on airborne sensing equipment to realize autonomous positioning in the ship’s surface environment of carrier-based aircraft in GPS-denied environment is the key technology that needs to be solved urgently. Therefore, an autonomous positioning algorithm is proposed for unmanned carrier-based aircraft based on visual and lider fusion. The algorithm performs multi-sensor online calibration by combining the hand-eye calibration and mutual information calibration methods, so that the unmanned carrier-based aircraft can still run stably after the fuselage shakes in the face of wind and waves and the operation of the aircraft carrier causes the sensor external parameter calibration results to change. A factor graph is introduced for multi-sensor pose joint optimization of unmanned carrier-borne aircraft, and a simple and efficient sensor failure criterion is established based on the motion model in the process of autonomous transport, so as to integrate the lidar and visual positioning results effectively so that the algorithm can operate stably even when a single sensor fails. Finally, a multi-sensor-based simulation system of carrier-based aircraft on the ship is established to verify the algorithm. Experimental results show that the positioning error of the algorithm remains within 0.2 m when a single sensor fails, which meets the requirements of practical applications.

Key words: unmanned carrier-based aircraft, multi-sensor fusion, autonomous positioning, online calibration, simulation of the ship’s surface

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