【摘 要】
:
卫星遮挡、信号干扰等复杂环境下,无人机器人的高可信定位与导航是实现其自主行驶的必要前提.本文针对由惯性测量单元(IMU)、全球卫星定位系统(GNSS)以及双目相机等构成的组合导航系统,采用传感器深组合模式,提出了一种基于增量平滑因子图的无人机器人可信导航方法.该方法首先通过构建各传感器及深度组合导航因子图模型,进行增量平滑优化,实现多传感器信息的高精度融合、传感器参数标定与视觉特征标注.在GNSS
【机 构】
:
空军研究院通信与导航研究所,北京,中国,100094 哈尔滨工业大学,哈尔滨,中国,150001
论文部分内容阅读
卫星遮挡、信号干扰等复杂环境下,无人机器人的高可信定位与导航是实现其自主行驶的必要前提.本文针对由惯性测量单元(IMU)、全球卫星定位系统(GNSS)以及双目相机等构成的组合导航系统,采用传感器深组合模式,提出了一种基于增量平滑因子图的无人机器人可信导航方法.该方法首先通过构建各传感器及深度组合导航因子图模型,进行增量平滑优化,实现多传感器信息的高精度融合、传感器参数标定与视觉特征标注.在GNSS拒止时,通过惯性测量单元与双目视觉的深组合,并利用获取的传感器参数、视觉特征等知识,实现了短时无人机器人的高精度定位导航.因子图的引入,实现了传感器的即时接入/退出,确保了导航模式的平滑切换.另一方面,该方法考虑多传感器之间的信息比对与校验,显著提高了定位导航的可信性.最后,通过构建数学仿真系统,设置多个场景开展本文所提方法的数学仿真,结果表明在GNSS可用时融合算法具有较高导航精度,并可对之间的导航状态进行较好地平滑;在GNSS拒止时,能够平稳切换,通过IMU与相机的组合实现较长时间的可信定位导航,全面验证了方法的有效性与算法的可信性.
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