You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
(m_x, m_y) - the position value as measured by the sensor converted to cartesian coordinates
2.(r_x, r_y, r_vx, r_vy) - the real ground truth state of the system(RMSE-Root mean square error)
in the ROS environment by using same source code with small changes like
(1)For ROS environment , i think need to use subscribe<sensor_msgs::Imu>(imu/data, 10,sensorCallback) for IMU data.
(2) Abstract lidar/Radar data from IMU like
L(for lidar) m_x m_y t r_x r_y r_vx r_vy
R(for radar) m_rho m_phi m_drho t r_px r_py r_vx r_vy
(3) Display the output like estimation and ground truth in ROS as shown in github link
How to Display the
2.(r_x, r_y, r_vx, r_vy) - the real ground truth state of the system(RMSE-Root mean square error)
in the ROS environment by using same source code with small changes like
(1)For ROS environment , i think need to use subscribe<sensor_msgs::Imu>(imu/data, 10,sensorCallback) for IMU data.
(2) Abstract lidar/Radar data from IMU like
L(for lidar) m_x m_y t r_x r_y r_vx r_vy
R(for radar) m_rho m_phi m_drho t r_px r_py r_vx r_vy
(3) Display the output like estimation and ground truth in ROS as shown in github link
I checked similar link https://github.com/cggos/imu_x_fusion. this repo and lidar_radar_fusion_ekf_ukf repo are different .imx_x_fusion difficult understand on EKF.
The text was updated successfully, but these errors were encountered: