因子图matlab代码-online-gpslam-code:论文代码“用于连续时间轨迹估计和映射的增量稀疏GP回归”

上传者: 38580759 | 上传时间: 2021-08-18 15:58:46 | 文件大小: 3.32MB | 文件类型: ZIP
因子图matlab代码欢迎来到online-gpslam [高斯过程|增量| GTSAM 3.2 | SLAM] 这是Incremental Sparse GP Regression for Continuous-time Trajectory Estimation and Mapping论文的代码库,作者:Yan Yanyan,Vadim Indelman和Byron Boots 介绍 该代码依赖于,它使用因子图和贝叶斯网络作为基础计算范例而非稀疏矩阵,在机器人技术和视觉中实现平滑和映射(SAM) 。 该代码由两部分组成: cpp :实现本文所用因素的c ++代码,包括: 2D高斯过程先验因子() LieVector的BearingRange系数() LieVector的范围因子() 插值范围系数() 预计速度因数() 插补速度因数() matlab :在本文中产生实验结果的matlab脚本。 我们对一个合成数据集和两个真实世界数据集进行了实验: 1,500个姿势的合成数据集 可在以下位置获得自动割草机广场数据集: 维多利亚公园的车辆数据集可在 尤其是,名称为XXX_periodic

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