6、代码解析 后端优化部分的代码主要在Estimator::optimization()这个函数中,我们来看看这个函数作了什么: 首先将vector转换为了数组的形式,因为ceres用的是double数组,所以下面用vector2double做类型转换 /*可以看出来,这里面生成的优化变量由: para_Pose(7维,相机位姿)、 para_SpeedBias(9维,相机速度、加速度偏置...
marginalization_info->marginalize(); // ROS_DEBUG("marginalization %f ms", t_margin.toc()); //---在optimization的最后会有一步滑窗预移动的操作 // 值得注意的是,这里仅仅是相当于将指针进行了一次移动,指针对应的数据还是旧数据,因此需要结合后面调用的 slideWindow() 函数才能实现真正的滑窗移动 std:...
因为大的捆集作为一个天然的缓冲区,它可以等待并且存储很长一段时间的测量值。工作Gomsf: Graph-optimization based multi-sensor fusion for robust uav pose estimation使用一种基于优化的框架来融合局部视觉惯性里程计(VIO)与GPS测量,这比工作A robust and modular multi-sensor fusion approach applied to mav nav...
【VINS论文笔记】A General Optimization-based Framework for Local Odometry Estimation with Multiple Sensors,程序员大本营,技术文章内容聚合第一站。
VINS-Fusion is an optimization-based multi-sensor state estimator, which achieves accurate self-localization for autonomous applications (drones, cars, and AR/VR). VINS-Fusion is an extension ofVINS-Mono, which supports multiple visual-inertial sensor types (mono camera + IMU, stereo cameras + IM...
本节主要讲loop_fusion包的程序结构,loop_fusion主要作用:利用词袋模型进行图像的回环检测。在vinsmono中,该程序包处于pose_graph包内。vins_fusion与vins_mono一个差别在于,回环检测的点云数据在mono中有回调供给VIO进行非线性优化,而在fusion中,VIO估计完全独立于回环检测的结果。即回环检测的全局估计会受到VIO的影响...
GlobalOptimization类 所有的融合算法都是在GlobalOptimization类中,对应的文件为globalOpt.h和globalOpt.cpp,并且ceres优化器的相关定义在Factors.h中。 GlobalOptimization类中的函数和变量如下 classGlobalOptimization {public: GlobalOptimization();~GlobalOptimization();voidinputGPS(doublet,doublelatitude,doublelongitude...
VINS-Fusion is an optimization-based multi-sensor state estimator, which achieves accurate self-localization for autonomous applications (drones, cars, and AR/VR). VINS-Fusion is an extension ofVINS-Mono, which supports multiple visual-inertial sensor types (mono camera + IMU, stereo cameras + IM...
VINS Fusion融合GPS和VIO数据的代码在global_fusion/src/globalOpt.cpp文件中,下面进行详细介绍。 a. 接收GPS数据,接收VIO数据并转到GPS坐标系 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 // 接收上面输入的vio数据 void GlobalOptimization::inputOdom(double t, Eigen::Vecto...
VINS-Fusion An optimization-based multi-sensor state estimator VINS-Fusion is an optimization-based multi-sensor state estimator, which achieves accurate self-localization for autonomous applications (drones, cars, and AR/VR). VINS-Fusion is an extension of VINS-Mono, which supports multiple visual-...