本文基于开源的VINS实现,里面用到IMU和RGB,本文扩展了框架,引入depth数据,并最终构建了RGBD inertial SLAM系统,用于地上机器人。本文主要的贡献: (1)为VINS-RGBD系统构建和实现集成depth的初始化过程。 (2)构建和实现集成depth的VIO,在仅有视觉或者视觉和IMU的场景,可以有一些提升。 (3)提供handheld,wheeled robot,...
(1)在catkin_ws的src文件夹内放入VINS-RGBD工程 (2)catkin_make编译 (3)打开terminal 1 roscore (4)terminal 2 source devel/setup.bash roslaunch vins_estimator realsense_color.launch (5)terminal3 source devel/setup.bash roslaunch vins_estimator vins_rviz.launch (6)terminal 4 rosbag play Simple.ba...
Dynamic-VINS估计的轨迹,红线是VINS-RGBD估计的轨迹,黄线表示在数据集结束时执行回环检测。 Abstract Current simultaneous localization and mapping(SLAM) algorithms perform well in static environments but easily fail in dynamic environments. Recent works introduce deep learning-based semantic information to SLAM ...
VINS-RGBDVINS-RGBD是一个基于深度学习的视觉惯性导航系统,它集成了深度相机(RGBD)和视觉传感器的数据。系统利用RGB图像和深度信息,通过实时的物体识别与图像匹配,结合IMU(惯性测量单元)数据,实现环境理解与导航。该模型着重于在室内或结构化环境中提供高精度的定位和姿态估计,适用于自动驾驶、机器人导航以及增强现实应用...
一种可支持RGB-D传感器的VINS-Fusion算法 1、可支持单目、双目、RGB-D与IMU的融合定位 RGBD在视觉跟踪时将特征点的参数化与双目相机一致,可实现静止状态的初始化。 2、使用RGB-D时可实现基于八叉树的稠密建图 实时生成局部三维稠密地图,地图可在图优化后进行修正,可保存关键帧的位姿图信息(带有三维稠密点云地图...
VINS-RGBD edited to run in Noetic environment (20.04) - VINS-RGBD-noetic/camera_model/CMakeLists.txt at master · U-AMC/VINS-RGBD-noetic
The performance of PLD-VINS is validated on public OpenLORIS-Scene datasets and real-world experiments. Comparing with other state-of-the-art algorithms, such as ORB-SLAM2, PL-VINS, VINS-RGBD, and so on, the proposed PLD-VINS is more exact, robust and reliable. (C) 2021 Elsevier Masson...
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The performance of PLD-VINS is validated on public OpenLORIS-Scene datasets and real-world experiments. Comparing with other state-of-the-art algorithms, such as ORB-SLAM2, PL-VINS, VINS-RGBD, and so on, the proposed PLD-VINS is more exact, robust and reliable. (C) 2021 Elsevier Masson...
Dynamic-VINS估计的轨迹,红线是VINS-RGBD估计的轨迹,黄线表示在数据集结束时执行回环检测。 Abstract Current simultaneous localization and mapping(SLAM) algorithms perform well in static environments but easily fail in dynamic environments. Recent works introduce deep learning-based semantic information to SLAM ...