visual odometry andmultiple view setting

最新推荐文章于 2021-11-11 15:45:03 发布
最新推荐文章于 2021-11-11 15:45:03 发布
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分类专栏： SLAM CV
博客围绕视觉里程计和多视图设置展开，虽未提供具体内容，但推测会涉及相关信息技术领域的原理、应用等关键信息。

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（九：2020.08.27）CVPR 2019 追踪之论文纲要（译）
Jojo论文基地
08-28 9264
CVPR 2019 追踪之论文纲要（修正于2020.08.28）讲在前面论文目录 讲在前面 论坛很多博客都对论文做了总结和分类，但就医学领域而言，对这些论文的筛选信息显然需要更加精细的把控，所以自己对这900篇的论文做一个大致从名称上的筛选，希望能找到些能解决当前问题的答案。 论文链接建议直接Google论文名，比去各种论文或顶会网站找不知道快捷多少。 下面皆为机器翻译，我会慢慢修正，但现在请结合。有兴趣的可以问我要处理这些论文并自动翻译的脚本。 Respect！ 论文目录 论文 概要
【CVPR2019】完整论文列表二
TomRen
06-11 8224
CVPR 2019 Paper list[1001-1294] CVPR2019 完整列表一 论文题目与链接 Semantic Component Decomposition for Face Attribute Manipulation R3 Adversarial Network for Cross Model Face Recognition Disentan...
【论文笔记】-- Visual Odometry Part I: The First 30 Years and Fundamentals
weixin_44832149的博客
05-06 1084
相较于SLAM十四讲，该论文对视觉里程计(VO)的介绍更加全面，尤其对一些常见的英文术语解释的很透彻。由于本人兴趣，只记录基于特征点的VO。
视觉里程入门Visual Odometry part1
10-12
Visual Odometry Part I: The First 30 Years and Fundamentals
A review of visual inertial odometry from filtering and optimisation perspectives
冬瓜大侠
06-10 1573
[1] Gui J, Gu D, Wang S, et al. A review of visual inertial odometry from filtering and optimisation perspectives[J]. Advanced Robotics, 2015, 29(20): 1289-1301. 红色标记为不确定是否正确，水平有限，欢迎指正。 摘要：视觉惯性里程...
高翔视觉slam十四讲（第二版）第13讲实践：设计slam系统遇到问题总结
kbfvictory的博客
07-12 4287
问题1：kitti数据集获取 方法：
NODES / joint_state_publisher (joint_state_publisher/joint_state_publisher) move_group (moveit_ros_move_group/move_group) robot_state_publisher (robot_state_publisher/robot_state_publisher) rviz_ubuntu_2861_4993542575836972810 (rviz/rviz) auto-starting new master process[master]: started with pid [2872] ROS_MASTER_URI=http://localhost:11311 setting /run_id to 1966f85e-0efb-11f0-850d-000c29c69146 process[rosout-1]: started with pid [2883] started core service [/rosout] process[joint_state_publisher-2]: started with pid [2886] process[robot_state_publisher-3]: started with pid [2891] ERROR: cannot launch node of type [moveit_ros_move_group/move_group]: moveit_ros_move_group ROS path [0]=/opt/ros/melodic/share/ros ROS path [1]=/home/fcy/catkin_ws/src ROS path [2]=/opt/ros/melodic/share process[rviz_ubuntu_2861_4993542575836972810-5]: started with pid [2892] [ INFO] [1743513208.619101648]: rviz version 1.13.30 [ INFO] [1743513208.619277497]: compiled against Qt version 5.9.5 [ INFO] [1743513208.619412670]: compiled against OGRE version 1.9.0 (Ghadamon) [ INFO] [1743513208.623547025]: Forcing OpenGl version 0. [ INFO] [1743513208.875174005]: Stereo is NOT SUPPORTED [ INFO] [1743513208.875654555]: OpenGL device: llvmpipe (LLVM 10.0.0, 256 bits) [ INFO] [1743513208.875857719]: OpenGl version: 3.1 (GLSL 1.4). [ERROR] [1743513209.002316614]: PluginlibFactory: The plugin for class 'moveit_rviz_plugin/MotionPlanning' failed to load. Error: According to the loaded plugin descriptions the class moveit_rviz_plugin/MotionPlanning with base class type rviz::Display does not exist. Declared types are rviz/Axes rviz/Camera rviz/DepthCloud rviz/Effort rviz/FluidPressure rviz/Grid rviz/GridCells rviz/Illuminance rviz/Image rviz/InteractiveMarkers rviz/LaserScan rviz/Map rviz/Marker rviz/MarkerArray rviz/Odometry rviz/Path rviz/PointCloud rviz/PointCloud2 rviz/PointStamped rviz/Polygon rviz/Pose rviz/PoseArray rviz/PoseWithCovariance rviz/Range rviz/RelativeHumidity rviz/RobotModel rviz/TF rviz/Temperature rviz/WrenchStamped rviz_plugin_tutorials/Imu
04-02
- TF树验证：使用`rosrun tf view_frames`生成坐标系关系图 - 轨迹可视化：在RViz中添加`MotionPlanning`显示模块（需修复插件后可用） 若问题持续，建议提供完整的launch文件内容和`robot_description`配置进行...
vae@vae-ASUS-TUF-Gaming-A15-FA507UU-FA507UU:~/primitive_ws/src/Primitive-Planner/src/scripts$ roslaunch primitive_planner swarm.launch ... logging to /home/vae/.ros/log/bd228878-6248-11f0-9b88-51c660762ec6/roslaunch-vae-ASUS-TUF-Gaming-A15-FA507UU-FA507UU-36532.log Checking log directory for disk usage. This may take a while. Press Ctrl-C to interrupt Done checking log file disk usage. Usage is <1GB. started roslaunch server http://vae-ASUS-TUF-Gaming-A15-FA507UU-FA507UU:40573/ SUMMARY ======== PARAMETERS * /drone_0_bridge_node/broadcast_ip: 127.0.0.255 * /drone_0_bridge_node/drone_id: 0 * /drone_0_bridge_node/odom_max_freq: 70 * /drone_0_odom_visualization/color/a: 1.0 * /drone_0_odom_visualization/color/b: 0.0 * /drone_0_odom_visualization/color/g: 0.0 * /drone_0_odom_visualization/color/r: 0.0 * /drone_0_odom_visualization/covariance_scale: 100.0 * /drone_0_odom_visualization/drone_id: 0 * /drone_0_odom_visualization/robot_scale: 0.24 * /drone_0_odom_visualization/tf45: False * /drone_0_pcl_render_node/cam_cx: 321.04638671875 * /drone_0_pcl_render_node/cam_cy: 243.44969177246094 * /drone_0_pcl_render_node/cam_fx: 387.229248046875 * /drone_0_pcl_render_node/cam_fy: 387.229248046875 * /drone_0_pcl_render_node/cam_height: 480 * /drone_0_pcl_render_node/cam_width: 640 * /drone_0_pcl_render_node/estimation_rate: 30.0 * /drone_0_pcl_render_node/map/x_size: 20.63661977236758 * /drone_0_pcl_render_node/map/y_size: 20.63661977236758 * /drone_0_pcl_render_node/map/z_size: 3.0 * /drone_0_pcl_render_node/sensing_horizon: 5.0 * /drone_0_pcl_render_node/sensing_rate: 10.0 * /drone_0_poscmd_2_odom/init_x: 0.3183098861837907 * /drone_0_poscmd_2_odom/init_y: 0.0 * /drone_0_poscmd_2_odom/init_z: 0.5 * /drone_0_primitive_planner_node/fsm/fail_safe: True * /drone_0_primitive_planner_node/fsm/flight_type: 2 * /drone_0_primitive_planner_node/fsm/no_replan_thresh: 0.5 * /drone_0_primitive_planner_node/fsm/realworld_experiment: True * /drone_0_primitive_planner_node/fsm/thresh_replan_time: 0.2 * /drone_0_primitive_planner_node/fsm/waypoint0_x: -0.3183098861837907 * /drone_0_primitive_planner_node/fsm/waypoint0_y: -0.0 * /drone_0_primitive_planner_node/fsm/waypoint0_z: 0.5 * /drone_0_primitive_planner_node/fsm/waypoint1_x: 0.0 * /drone_0_primitive_planner_node/fsm/waypoint1_y: 0.0 * /drone_0_primitive_planner_node/fsm/waypoint1_z: 0.0 * /drone_0_primitive_planner_node/fsm/waypoint2_x: 0.0 * /drone_0_primitive_planner_node/fsm/waypoint2_y: 0.0 * /drone_0_primitive_planner_node/fsm/waypoint2_z: 0.0 * /drone_0_primitive_planner_node/fsm/waypoint_num: 1 * /drone_0_primitive_planner_node/manager/arc_length: 3.0 * /drone_0_primitive_planner_node/manager/boxX: 6.0 * /drone_0_primitive_planner_node/manager/boxY: 6.0 * /drone_0_primitive_planner_node/manager/boxZ: 6.0 * /drone_0_primitive_planner_node/manager/depthCloudStackNum: 1 * /drone_0_primitive_planner_node/manager/drone_id: 0 * /drone_0_primitive_planner_node/manager/lamda_b: 50.0 * /drone_0_primitive_planner_node/manager/lamda_l: 200.0 * /drone_0_primitive_planner_node/manager/map_size_x: 20.63661977236758 * /drone_0_primitive_planner_node/manager/map_size_y: 20.63661977236758 * /drone_0_primitive_planner_node/manager/map_size_z: 3.0 * /drone_0_primitive_planner_node/manager/max_vel: 1.0 * /drone_0_primitive_planner_node/manager/primitiveFolder: /home/vae/primiti... * /drone_0_primitive_planner_node/manager/sampleSize: 10000 * /drone_0_primitive_planner_node/manager/swarm_clearence: 0.24 * /drone_0_primitive_planner_node/manager/voxelSize: 0.1 * /drone_0_traj_server/init_x: 0.3183098861837907 * /drone_0_traj_server/init_y: 0.0 * /drone_0_traj_server/init_z: 0.5 * /drone_0_traj_server/traj_server/max_vel: 1.0 * /drone_0_traj_server/traj_server/primitiveFolder: /home/vae/primiti... * /drone_0_traj_server/traj_server/time_delay_idx: 0 * /drone_0_traj_server/traj_server/time_forward: 1.0 * /random_forest/ObstacleShape/lower_hei: 0.0 * /random_forest/ObstacleShape/lower_rad: 0.2 * /random_forest/ObstacleShape/radius_h: 0.5 * /random_forest/ObstacleShape/radius_l: 0.7 * /random_forest/ObstacleShape/theta: 0.5 * /random_forest/ObstacleShape/upper_hei: 3.0 * /random_forest/ObstacleShape/upper_rad: 0.5 * /random_forest/ObstacleShape/z_h: 0.8 * /random_forest/ObstacleShape/z_l: 0.7 * /random_forest/map/circle_num: 0.46484179349639226 * /random_forest/map/obs_num: 0.46484179349639226 * /random_forest/map/resolution: 0.1 * /random_forest/map/x_size: -0.9642010096410315 * /random_forest/map/y_size: -0.9642010096410315 * /random_forest/map/z_size: 3.0 * /random_forest/min_distance: 0.8 * /random_forest/pub_rate: 1.0 * /rosdistro: noetic * /rosversion: 1.17.4 NODES / drone_0_bridge_node (swarm_bridge/bridge_node_udp) drone_0_odom_visualization (odom_visualization/odom_visualization) drone_0_pcl_render_node (local_sensing_node/pcl_render_node) drone_0_poscmd_2_odom (poscmd_2_odom/poscmd_2_odom) drone_0_primitive_planner_node (primitive_planner/primitive_planner_node) drone_0_traj_server (primitive_planner/traj_server) random_forest (map_generator/random_forest) rviz (rviz/rviz) auto-starting new master process[master]: started with pid [36557] ROS_MASTER_URI=http://localhost:11311 setting /run_id to bd228878-6248-11f0-9b88-51c660762ec6 process[rosout-1]: started with pid [36582] started core service [/rosout] process[drone_0_bridge_node-2]: started with pid [36589] process[random_forest-3]: started with pid [36590] process[rviz-4]: started with pid [36591] process[drone_0_primitive_planner_node-5]: started with pid [36597] process[drone_0_traj_server-6]: started with pid [36599] process[drone_0_poscmd_2_odom-7]: started with pid [36600] process[drone_0_odom_visualization-8]: started with pid [36601] process[drone_0_pcl_render_node-9]: started with pid [36611] [ERROR] [1752672500.302585947]: Illegal pathID=-1 [rosmsg_tcp_bridge] start running [drone_0_primitive_planner_node-5] process has finished cleanly log file: /home/vae/.ros/log/bd228878-6248-11f0-9b88-51c660762ec6/drone_0_primitive_planner_node-5*.log [WARN] [1752672500.791081325]: Finished generate random map [pcl::KdTreeFLANN::setInputCloud] Cannot create a KDTree with an empty input cloud! [WARN] [1752672500.794334498]: Global Pointcloud received.. [pcl::KdTreeFLANN::setInputCloud] Cannot create a KDTree with an empty input cloud! [drone_0_pcl_render_node-9] process has died [pid 36611, exit code -11, cmd /home/vae/primitive_ws/devel/lib/local_sensing_node/pcl_render_node ~global_map:=/map_generator/global_cloud ~odometry:=/drone_0_visual_slam/odom ~pcl_render_node/cloud:=/drone_0_pcl_render_node/cloud __name:=drone_0_pcl_render_node __log:=/home/vae/.ros/log/bd228878-6248-11f0-9b88-51c660762ec6/drone_0_pcl_render_node-9.log]. log file: /home/vae/.ros/log/bd228878-6248-11f0-9b88-51c660762ec6/drone_0_pcl_render_node-9*.log [INFO] [1752672501.293613925]: [Traj server]: ready. [rospack] Error: failed to parse command-line options: too many positional options have been specified on the command line [librospack]: error while executing command [rospack] Error: failed to parse command-line options: too many positional options have been specified on the command line [librospack]: error while executing command [rospack] Error: failed to parse command-line options: too many positional options have been specified on the command line [librospack]: error while executing command [WARN] [1752672547.878321128]: Shutdown request received. [WARN] [1752672547.878370290]: Reason given for shutdown: [user request] [random_forest-3] process has finished cleanly log file: /home/vae/.ros/log/bd228878-6248-11f0-9b88-51c660762ec6/random_forest-3*.log
最新发布
07-17
rosrun tf view_frames # 生成TF树PDF evince frames.pdf # 查看坐标系连接 ``` 确保`map`→`odom`→`base_link`链路完整[^4]。 2. **验证目标点有效性**： ```bash rostopic echo /move_base/goal # 检查...
自动驾驶最全基础知识、课程、论文、数据集、开源软件等资源整理分享
lqfarmer的博客
08-15 2843
自动驾驶汽车（Autonomous vehicles）又称无人驾驶汽车、电脑驾驶汽车、或轮式移动机器人，是一种通过电脑系统实现无人驾驶的智能汽车。在20世纪已有数十年的历史，21世纪初呈现出接近实用化的趋势。自动驾驶汽车依靠人工智能、视觉计算、雷达、监控装置和全球定位系统协同合作，让电脑可以在没有任何人类主动的操作下，自动安全地操作机动车辆。 资源整理自网络，源地址：https://github.com/manfreddiaz/awesome-autonomous-vehicles ...
Consistency Analysis for Sliding-Window Visual Odometry
04-02
本文详细分析了基于滑动窗口的视觉slam或者视觉里程计方案的一致性问题
视觉里程入门Visual Odometry part2
10-12
Visual Odometry Part II: Matching, Robustness, Optimization, and Applications
data_12468
06-20
编程实例
kitti数据集百度网盘地址
10-22
已经下载好了的kitti数据集，用于自动驾驶、目标检测、深度学习
【转】SLAM 论文阅读和分类整理
世事洞明皆学问
04-17 2673
需要时不时膜拜一下大神，激发一下原动力！！！ 前言：以前读论文，都是靠脑子硬记，哪个实验室，谁，哪一年在什么会议上发了一篇关于什么的论文。当需要回溯的时候，每篇论文能给出个大概，不具体，找起来也麻烦，以后就在这个 List 里分类整理已经读过的论文。之前读的，以及后续的一些新的有意义的论文都会慢慢补充进来 (汗, 感觉会是一个非常长的 list)。 基础知识材料 2018年, joan sol...
基于关键帧视觉惯性传感器非线性优化SLAM
枫叶南国的博客
04-21 7927
Keyframe-Based Visual-Inertial SLAM Using Nonlinear Optimization Taylor Guo, 2016年4月13日-12:01  – 2016年8月1日-20：30  @ EJU Shanghai 原文发表于Conference :《 Robotics: Science and Systems (RSS)》, 2013-06-24
多传感器融合定位开源工程与论文
老李的博客
11-11 6831
目录(1)LIC-Fusion：基于激光雷达、惯性导航和相机结合的里程计(2)使用点线特征配合激光雷达辅助的单目视觉里程计(3)间歇的GPS辅助VIO：在线初始化和标定(4)强大的高精度视觉惯性激光SLAM系统(5)地面机器人的视觉辅助定位**(6)松耦合的半直接法单目SLAM(7)双目视觉惯性雷达VIL-SLAM (1)LIC-Fusion：基于激光雷达、惯性导航和相机结合的里程计 标题：LIC-Fusion: LiDAR-Inertial-Camera Odometry 作者：Xingxing Zuo
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