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作 者:吴建峰[1,2] 程向红 WU Jianfeng;CHENG Xianghong(Key Laboratory of Micro-inertial Instrument and Advanced Navigation Technology,Ministry of Education,Southeast University,Nanjing 210096,China;School of Instrument Science&Engineering,Southeast University,Nanjing 210096,China)
机构地区:[1]微惯性仪表与先进导航技术教育部重点实验室,南京210096 [2]东南大学仪器科学与工程学院,南京210096
出 处:《中国惯性技术学报》2024年第5期463-467,共5页Journal of Chinese Inertial Technology
基 金:国家自然科学基金项目(6227021193)。
摘 要:视觉惯性导航系统在初始化阶段解算出系统初始位姿、惯性测量单元(IMU)零偏以及单目尺度因子,能极大程度上保证系统收敛。为解决视觉惯性导航系统在点特征缺失环境下初始化效果差甚至失败的问题,提出了一种基于点线的视觉惯性导航系统初始化方法。首先,通过几何方法在滑动窗口内构造了一个基于点线的结构,该结构相比于点结构具有更丰富的先验信息;其次,使用从运动中恢复结构(Sf M)的方法,恢复点线结构的运动状态;最后,以松组合的形式对齐结构的运动状态以及IMU预积分结果,求解出IMU零偏、重力加速度、速度和尺度因子等初始量。实验结果表明:在点特征缺失的公共数据集上,相较于基于点特征的初始化方法,所提方法的均方根定位误差减少6%,初始误差显著降低,同时具有更好的建图结果。The visual inertial navigation system calculates the initial pose,inertial measurement unit(IMU)bias,and monocular scale factor during the initialization phase,which can greatly ensure system convergence.To address the issue of poor or even failed initialization of visual inertial navigation systems in environments with missing point features,an initialization method for visual inertial navigation system based on point line is proposed.Firstly,a point line based structure is constructed within the sliding window using geometric methods,which has richer prior information compared to point structures.Secondly,the method of restoring structure from motion(SfM)is used to restore the motion state of the point line structure.Finally,align the motion state of the structure and the IMU pre integration results in a loose combination form,and solve for the initial variables such as IMU bias,gravitational acceleration,velocity,and scale factor.The experimental results show that on the public dataset with missing point features,compared to the original algorithm,the proposed method reduces the root mean square localization error by 6%,significantly reduces the initial error,and has better mapping results.
分 类 号:U666.1[交通运输工程—船舶及航道工程]
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