之前博客《ROS实验笔记之——Intel Realsense l515激光相机的使用》实现了用l515运行RTABmap，本博文试试在l515上实现vins-mono

首先需要将vins-mono配置成功，如果出现像之前博客《ROS实验笔记之——SLAM无人驾驶初入门》提到的运行出错的问题也只能按里面的方法改改了。。。。

首先可以先运行

roslaunch realsense2_camera rs_camera.launch

看对应的launch文件

<launch><arg name="serial_no"           default=""/><arg name="usb_port_id"         default=""/><arg name="device_type"         default=""/><arg name="json_file_path"      default=""/><arg name="camera"              default="camera"/><arg name="tf_prefix"           default="$(arg camera)"/><arg name="external_manager"    default="false"/><arg name="manager"             default="realsense2_camera_manager"/><arg name="output"              default="screen"/><arg name="respawn"              default="false"/><arg name="fisheye_width"       default="-1"/><arg name="fisheye_height"      default="-1"/><arg name="enable_fisheye"      default="false"/><arg name="depth_width"         default="-1"/><arg name="depth_height"        default="-1"/><arg name="enable_depth"        default="true"/><arg name="confidence_width"    default="-1"/><arg name="confidence_height"   default="-1"/><arg name="enable_confidence"   default="true"/><arg name="confidence_fps"      default="-1"/><arg name="infra_width"         default="848"/><arg name="infra_height"        default="480"/><arg name="enable_infra"        default="false"/><arg name="enable_infra1"       default="false"/><arg name="enable_infra2"       default="false"/><arg name="infra_rgb"           default="false"/><arg name="color_width"         default="-1"/><arg name="color_height"        default="-1"/><arg name="enable_color"        default="true"/><arg name="fisheye_fps"         default="-1"/><arg name="depth_fps"           default="-1"/><arg name="infra_fps"           default="30"/><arg name="color_fps"           default="-1"/><arg name="gyro_fps"            default="-1"/><arg name="accel_fps"           default="-1"/><arg name="enable_gyro"         default="false"/><arg name="enable_accel"        default="false"/><arg name="enable_pointcloud"         default="false"/><arg name="pointcloud_texture_stream" default="RS2_STREAM_COLOR"/><arg name="pointcloud_texture_index"  default="0"/><arg name="allow_no_texture_points"   default="false"/><arg name="ordered_pc"                default="false"/><arg name="enable_sync"               default="false"/><arg name="align_depth"               default="false"/><arg name="publish_tf"                default="true"/><arg name="tf_publish_rate"           default="0"/><arg name="filters"                   default=""/><arg name="clip_distance"             default="-2"/><arg name="linear_accel_cov"          default="0.01"/><arg name="initial_reset"             default="false"/><arg name="unite_imu_method"          default=""/><arg name="topic_odom_in"             default="odom_in"/><arg name="calib_odom_file"           default=""/><arg name="publish_odom_tf"           default="true"/><arg name="stereo_module/exposure/1"  default="7500"/><arg name="stereo_module/gain/1"      default="16"/><arg name="stereo_module/exposure/2"  default="1"/><arg name="stereo_module/gain/2"      default="16"/><group ns="$(arg camera)"><include file="$(find realsense2_camera)/launch/includes/nodelet.launch.xml"><arg name="tf_prefix"                value="$(arg tf_prefix)"/><arg name="external_manager"         value="$(arg external_manager)"/><arg name="manager"                  value="$(arg manager)"/><arg name="output"                   value="$(arg output)"/><arg name="respawn"                  value="$(arg respawn)"/><arg name="serial_no"                value="$(arg serial_no)"/><arg name="usb_port_id"              value="$(arg usb_port_id)"/><arg name="device_type"              value="$(arg device_type)"/><arg name="json_file_path"           value="$(arg json_file_path)"/><arg name="enable_pointcloud"        value="$(arg enable_pointcloud)"/><arg name="pointcloud_texture_stream" value="$(arg pointcloud_texture_stream)"/><arg name="pointcloud_texture_index"  value="$(arg pointcloud_texture_index)"/><arg name="enable_sync"              value="$(arg enable_sync)"/><arg name="align_depth"              value="$(arg align_depth)"/><arg name="fisheye_width"            value="$(arg fisheye_width)"/><arg name="fisheye_height"           value="$(arg fisheye_height)"/><arg name="enable_fisheye"           value="$(arg enable_fisheye)"/><arg name="depth_width"              value="$(arg depth_width)"/><arg name="depth_height"             value="$(arg depth_height)"/><arg name="enable_depth"             value="$(arg enable_depth)"/><arg name="confidence_width"         value="$(arg confidence_width)"/><arg name="confidence_height"        value="$(arg confidence_height)"/><arg name="enable_confidence"        value="$(arg enable_confidence)"/><arg name="confidence_fps"           value="$(arg confidence_fps)"/><arg name="color_width"              value="$(arg color_width)"/><arg name="color_height"             value="$(arg color_height)"/><arg name="enable_color"             value="$(arg enable_color)"/><arg name="infra_width"              value="$(arg infra_width)"/><arg name="infra_height"             value="$(arg infra_height)"/><arg name="enable_infra"             value="$(arg enable_infra)"/><arg name="enable_infra1"            value="$(arg enable_infra1)"/><arg name="enable_infra2"            value="$(arg enable_infra2)"/><arg name="infra_rgb"                value="$(arg infra_rgb)"/><arg name="fisheye_fps"              value="$(arg fisheye_fps)"/><arg name="depth_fps"                value="$(arg depth_fps)"/><arg name="infra_fps"                value="$(arg infra_fps)"/><arg name="color_fps"                value="$(arg color_fps)"/><arg name="gyro_fps"                 value="$(arg gyro_fps)"/><arg name="accel_fps"                value="$(arg accel_fps)"/><arg name="enable_gyro"              value="$(arg enable_gyro)"/><arg name="enable_accel"             value="$(arg enable_accel)"/><arg name="publish_tf"               value="$(arg publish_tf)"/><arg name="tf_publish_rate"          value="$(arg tf_publish_rate)"/><arg name="filters"                  value="$(arg filters)"/><arg name="clip_distance"            value="$(arg clip_distance)"/><arg name="linear_accel_cov"         value="$(arg linear_accel_cov)"/><arg name="initial_reset"            value="$(arg initial_reset)"/><arg name="unite_imu_method"         value="$(arg unite_imu_method)"/><arg name="topic_odom_in"            value="$(arg topic_odom_in)"/><arg name="calib_odom_file"          value="$(arg calib_odom_file)"/><arg name="publish_odom_tf"          value="$(arg publish_odom_tf)"/><arg name="stereo_module/exposure/1" value="$(arg stereo_module/exposure/1)"/><arg name="stereo_module/gain/1"     value="$(arg stereo_module/gain/1)"/><arg name="stereo_module/exposure/2" value="$(arg stereo_module/exposure/2)"/><arg name="stereo_module/gain/2"     value="$(arg stereo_module/gain/2)"/><arg name="allow_no_texture_points"  value="$(arg allow_no_texture_points)"/><arg name="ordered_pc"               value="$(arg ordered_pc)"/></include></group>
</launch>

查看一下topic

rostopic list
/camera/color/camera_info
/camera/color/image_raw
/camera/color/image_raw/compressed
/camera/color/image_raw/compressed/parameter_descriptions
/camera/color/image_raw/compressed/parameter_updates
/camera/color/image_raw/compressedDepth
/camera/color/image_raw/compressedDepth/parameter_descriptions
/camera/color/image_raw/compressedDepth/parameter_updates
/camera/color/image_raw/theora
/camera/color/image_raw/theora/parameter_descriptions
/camera/color/image_raw/theora/parameter_updates
/camera/depth/camera_info
/camera/depth/image_rect_raw
/camera/depth/image_rect_raw/compressed
/camera/depth/image_rect_raw/compressed/parameter_descriptions
/camera/depth/image_rect_raw/compressed/parameter_updates
/camera/depth/image_rect_raw/compressedDepth
/camera/depth/image_rect_raw/compressedDepth/parameter_descriptions
/camera/depth/image_rect_raw/compressedDepth/parameter_updates
/camera/depth/image_rect_raw/theora
/camera/depth/image_rect_raw/theora/parameter_descriptions
/camera/depth/image_rect_raw/theora/parameter_updates
/camera/extrinsics/depth_to_color
/camera/l500_depth_sensor/parameter_descriptions
/camera/l500_depth_sensor/parameter_updates
/camera/motion_module/parameter_descriptions
/camera/motion_module/parameter_updates
/camera/realsense2_camera_manager/bond
/camera/rgb_camera/parameter_descriptions
/camera/rgb_camera/parameter_updates
/diagnostics
/rosout
/rosout_agg
/tf
/tf_static

没有发现有IMU，该一下命令为：

roslaunch realsense2_camera rs_camera.launch \align_depth:=true \unite_imu_method:="linear_interpolation" \enable_gyro:=true \enable_accel:=true

rostopic list
/camera/accel/imu_info
/camera/align_to_color/parameter_descriptions
/camera/align_to_color/parameter_updates
/camera/aligned_depth_to_color/camera_info
/camera/aligned_depth_to_color/image_raw
/camera/aligned_depth_to_color/image_raw/compressed
/camera/aligned_depth_to_color/image_raw/compressed/parameter_descriptions
/camera/aligned_depth_to_color/image_raw/compressed/parameter_updates
/camera/aligned_depth_to_color/image_raw/compressedDepth
/camera/aligned_depth_to_color/image_raw/compressedDepth/parameter_descriptions
/camera/aligned_depth_to_color/image_raw/compressedDepth/parameter_updates
/camera/aligned_depth_to_color/image_raw/theora
/camera/aligned_depth_to_color/image_raw/theora/parameter_descriptions
/camera/aligned_depth_to_color/image_raw/theora/parameter_updates
/camera/color/camera_info
/camera/color/image_raw
/camera/color/image_raw/compressed
/camera/color/image_raw/compressed/parameter_descriptions
/camera/color/image_raw/compressed/parameter_updates
/camera/color/image_raw/compressedDepth
/camera/color/image_raw/compressedDepth/parameter_descriptions
/camera/color/image_raw/compressedDepth/parameter_updates
/camera/color/image_raw/theora
/camera/color/image_raw/theora/parameter_descriptions
/camera/color/image_raw/theora/parameter_updates
/camera/depth/camera_info
/camera/depth/image_rect_raw
/camera/depth/image_rect_raw/compressed
/camera/depth/image_rect_raw/compressed/parameter_descriptions
/camera/depth/image_rect_raw/compressed/parameter_updates
/camera/depth/image_rect_raw/compressedDepth
/camera/depth/image_rect_raw/compressedDepth/parameter_descriptions
/camera/depth/image_rect_raw/compressedDepth/parameter_updates
/camera/depth/image_rect_raw/theora
/camera/depth/image_rect_raw/theora/parameter_descriptions
/camera/depth/image_rect_raw/theora/parameter_updates
/camera/extrinsics/depth_to_color
/camera/gyro/imu_info
/camera/imu
/camera/l500_depth_sensor/parameter_descriptions
/camera/l500_depth_sensor/parameter_updates
/camera/motion_module/parameter_descriptions
/camera/motion_module/parameter_updates
/camera/realsense2_camera_manager/bond
/camera/rgb_camera/parameter_descriptions
/camera/rgb_camera/parameter_updates
/diagnostics
/rosout
/rosout_agg
/tf
/tf_static

就可以发现其将imu分成了两个：
“/camera/gyro/imu_info” 发布角速度
“/camera/accel/imu_info” 发布线加速度

但同时，也有

“/camera/imu”所以应该就不需要改动什么了。

同时还应该让imu与camera同步

roslaunch realsense2_camera rs_camera.launch \align_depth:=true \unite_imu_method:="linear_interpolation" \enable_gyro:=true \enable_accel:=true \enable_sync:=true

然后就设置vins。首先在realsense_color_config.yaml基础上修改订阅的topic

#common parameters
# imu_topic: "/camera/imu/data_raw"
# image_topic: "/camera/color/image_raw"
imu_topic: "/camera/imu"
image_topic: "/camera/color/image_raw"

相机的内参，通过读取camera_info得到或者自己标定，采用以下命令可以读取厂家的camera_info，但与实际可能存在差距。

rostopic echo /camera/color/camera_info

相机到IMU的变换矩阵

# Extrinsic parameter between IMU and Camera.
estimate_extrinsic: 0   # 0  Have an accurate extrinsic parameters. We will trust the following imu^R_cam, imu^T_cam, don't change it.# 1  Have an initial guess about extrinsic parameters. We will optimize around your initial guess.# 2  Don't know anything about extrinsic parameters. You don't need to give R,T. We will try to calibrate it. Do some rotation movement at beginning.
#If you choose 0 or 1, you should write down the following matrix.

这里IMU和camera之间的外参矩阵建议使用Kalibr工具进行离线标定，也可以改成1或者2让估计器自己标定和优化。此处设定为2

realsense l515说是已经做好了硬件同步所以不需要在线估计同步时差（但是用kalibr标定出来和在线估计出来都存在大概-0.06的时间差）

#unsynchronization parameters
estimate_td: 0                      # online estimate time offset between camera and imu
td: 0.000                           # initial value of time offset. unit: s. readed image clock + td = real image clock (IMU clock)

相机曝光方式应为全局曝光

#rolling shutter parameters
rolling_shutter: 0                      # 0: global shutter camera, 1: rolling shutter camera
rolling_shutter_tr: 0               # unit: s. rolling shutter read out time per frame (from data sheet).

然后就可以运行了

roslaunch realsense2_camera rs_camera.launch \align_depth:=true \unite_imu_method:="copy" \enable_gyro:=true \enable_accel:=true \enable_sync:=trueroslaunch vins_estimator realsense_color.launch
roslaunch vins_estimator vins_rviz.launch

好像不太行。。。换台电脑试试终于可以了。。。但是运动一段时间后，会飘得很严重，详见下面视频

vins

%YAML:1.0#common parameters
imu_topic: "/camera/imu"
image_topic: "/camera/color/image_raw"
output_path: "/home/tony-ws1/output/"#camera calibration
model_type: PINHOLE
camera_name: camera
image_width: 1280
image_height: 720
distortion_parameters:k1: 9.2615504465028850e-02k2: -1.8082438825995681e-01p1: -6.5484100374765971e-04p2: -3.5829351558557421e-04
projection_parameters:fx: 6.0970550296798035e+02fy: 6.0909579671294716e+02cx: 3.1916667152289227e+02cy: 2.3558360480225772e+02# Extrinsic parameter between IMU and Camera.
estimate_extrinsic: 2   # 0  Have an accurate extrinsic parameters. We will trust the following imu^R_cam, imu^T_cam, don't change it.# 1  Have an initial guess about extrinsic parameters. We will optimize around your initial guess.# 2  Don't know anything about extrinsic parameters. You don't need to give R,T. We will try to calibrate it. Do some rotation movement at beginning.
#If you choose 0 or 1, you should write down the following matrix.
#Rotation from camera frame to imu frame, imu^R_cam
extrinsicRotation: !!opencv-matrixrows: 3cols: 3dt: ddata: [ 0.99964621,  0.01105994,  0.02418954,-0.01088975,  0.9999151,  -0.00715601, -0.02426663,  0.00689006,  0.99968178]
#Translation from camera frame to imu frame, imu^T_cam
extrinsicTranslation: !!opencv-matrixrows: 3cols: 1dt: ddata: [0.07494282, -0.01077138, -0.00641822]#feature traker paprameters
max_cnt: 150            # max feature number in feature tracking
min_dist: 25            # min distance between two features
freq: 10                # frequence (Hz) of publish tracking result. At least 10Hz for good estimation. If set 0, the frequence will be same as raw image
F_threshold: 1.0        # ransac threshold (pixel)
show_track: 1           # publish tracking image as topic
equalize: 0             # if image is too dark or light, trun on equalize to find enough features
fisheye: 0              # if using fisheye, trun on it. A circle mask will be loaded to remove edge noisy points#optimization parameters
max_solver_time: 0.04  # max solver itration time (ms), to guarantee real time
max_num_iterations: 8   # max solver itrations, to guarantee real time
keyframe_parallax: 10.0 # keyframe selection threshold (pixel)#imu parameters       The more accurate parameters you provide, the better performance
acc_n: 0.1          # accelerometer measurement noise standard deviation. #0.2
gyr_n: 0.01         # gyroscope measurement noise standard deviation.     #0.05
acc_w: 0.0002         # accelerometer bias random work noise standard deviation.  #0.02
gyr_w: 2.0e-5       # gyroscope bias random work noise standard deviation.     #4.0e-5
g_norm: 9.805       # gravity magnitude#loop closure parameters
loop_closure: 1                    # start loop closure
fast_relocalization: 1             # useful in real-time and large project
load_previous_pose_graph: 0        # load and reuse previous pose graph; load from 'pose_graph_save_path'
pose_graph_save_path: "/home/tony-ws1/output/pose_graph/" # save and load path#unsynchronization parameters
estimate_td: 1                     # online estimate time offset between camera and imu
td: 0.000                           # initial value of time offset. unit: s. readed image clock + td = real image clock (IMU clock)#rolling shutter parameters
rolling_shutter: 1                      # 0: global shutter camera, 1: rolling shutter camera
rolling_shutter_tr: 0.033               # unit: s. rolling shutter read out time per frame (from data sheet). #visualization parameters
save_image: 1                   # save image in pose graph for visualization prupose; you can close this function by setting 0
visualize_imu_forward: 0        # output imu forward propogation to achieve low latency and high frequence results
visualize_camera_size: 0.4      # size of camera marker in RVIZ

实现了之后发现还是会漂，感觉对相机进行矫正是非常有必要的，但是确又不知道各个参数的意义，终于在连接中找到了（https://github.com/HKPolyU-UAV/FLVIS）

原创 | 《相机标定》深入理解原理与实战（一）

header: seq: 21stamp: secs: 1632650051nsecs: 413622856frame_id: "camera_color_optical_frame"
height: 720
width: 1280
distortion_model: "plumb_bob"
D: [0.14218834042549133, -0.48622673749923706, 0.0013360617449507117, 0.0007612911867909133, 0.444832980632782]
K: [905.8331298828125, 0.0, 649.684814453125, 0.0, 905.6519775390625, 352.701416015625, 0.0, 0.0, 1.0]
R: [1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0]
P: [905.8331298828125, 0.0, 649.684814453125, 0.0, 0.0, 905.6519775390625, 352.701416015625, 0.0, 0.0, 0.0, 1.0, 0.0]
binning_x: 0
binning_y: 0
roi: x_offset: 0y_offset: 0height: 0width: 0do_rectify: False
---

image_width: 1280
image_height: 720
cam0_intrinsics: [905.8331298828125, 905.6519775390625, 649.684814453125, 352.701416015625]#fx fy cx cy
cam0_distortion_coeffs: [0.14218834042549133, -0.48622673749923706, 0.0013360617449507117, 0.0007612911867909133]#k1 k2 p1 p2

（所以对于镜头畸变一共有 5 个参数 k1, k2, k3, p1, p2 需要校准，这 5 个参数和 M1 一起，都是需要标定的相机内参。opencv 输出的即便参数顺序是 k1, k2, p1, p2, k3 因为 k3 没那么重要。）

采用标定的参数修改一下有：

%YAML:1.0#common parameters
imu_topic: "/camera/imu"
image_topic: "/camera/color/image_raw"
output_path: "/home/tony-ws1/output/"#camera calibration
model_type: PINHOLE
camera_name: camera
image_width: 1280
image_height: 720
distortion_parameters:k1: 0.14218834042549133k2: -0.48622673749923706p1: 0.0013360617449507117p2:  0.0007612911867909133
projection_parameters:fx: 905.8331298828125fy: 905.6519775390625cx: 649.684814453125cy: 352.701416015625# Extrinsic parameter between IMU and Camera.
estimate_extrinsic: 2   # 0  Have an accurate extrinsic parameters. We will trust the following imu^R_cam, imu^T_cam, don't change it.# 1  Have an initial guess about extrinsic parameters. We will optimize around your initial guess.# 2  Don't know anything about extrinsic parameters. You don't need to give R,T. We will try to calibrate it. Do some rotation movement at beginning.
#If you choose 0 or 1, you should write down the following matrix.
#Rotation from camera frame to imu frame, imu^R_cam
extrinsicRotation: !!opencv-matrixrows: 3cols: 3dt: ddata: [ 0.99964621,  0.01105994,  0.02418954,-0.01088975,  0.9999151,  -0.00715601, -0.02426663,  0.00689006,  0.99968178]
#Translation from camera frame to imu frame, imu^T_cam
extrinsicTranslation: !!opencv-matrixrows: 3cols: 1dt: ddata: [0.07494282, -0.01077138, -0.00641822]#feature traker paprameters
max_cnt: 150            # max feature number in feature tracking
min_dist: 25            # min distance between two features
freq: 10                # frequence (Hz) of publish tracking result. At least 10Hz for good estimation. If set 0, the frequence will be same as raw image
F_threshold: 1.0        # ransac threshold (pixel)
show_track: 1           # publish tracking image as topic
equalize: 0             # if image is too dark or light, trun on equalize to find enough features
fisheye: 0              # if using fisheye, trun on it. A circle mask will be loaded to remove edge noisy points#optimization parameters
max_solver_time: 0.04  # max solver itration time (ms), to guarantee real time
max_num_iterations: 8   # max solver itrations, to guarantee real time
keyframe_parallax: 10.0 # keyframe selection threshold (pixel)#imu parameters       The more accurate parameters you provide, the better performance
acc_n: 0.1          # accelerometer measurement noise standard deviation. #0.2
gyr_n: 0.01         # gyroscope measurement noise standard deviation.     #0.05
acc_w: 0.0002         # accelerometer bias random work noise standard deviation.  #0.02
gyr_w: 2.0e-5       # gyroscope bias random work noise standard deviation.     #4.0e-5
g_norm: 9.805       # gravity magnitude#loop closure parameters
loop_closure: 1                    # start loop closure
fast_relocalization: 1             # useful in real-time and large project
load_previous_pose_graph: 0        # load and reuse previous pose graph; load from 'pose_graph_save_path'
pose_graph_save_path: "/home/tony-ws1/output/pose_graph/" # save and load path#unsynchronization parameters
estimate_td: 1                     # online estimate time offset between camera and imu
td: 0.000                           # initial value of time offset. unit: s. readed image clock + td = real image clock (IMU clock)#rolling shutter parameters
rolling_shutter: 1                      # 0: global shutter camera, 1: rolling shutter camera
rolling_shutter_tr: 0.033               # unit: s. rolling shutter read out time per frame (from data sheet). #visualization parameters
save_image: 1                   # save image in pose graph for visualization prupose; you can close this function by setting 0
visualize_imu_forward: 0        # output imu forward propogation to achieve low latency and high frequence results
visualize_camera_size: 0.4      # size of camera marker in RVIZ

好像还是不行。。。imu飘得好厉害

参考资料

如何用Realsense D435i运行VINS-Mono等VIO算法获取IMU同步数据_Manii-CSDN博客https://blog.csdn.net/qq_41839222/article/details/86552367

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