Hello, I'm very new in Kalman filter and I'm trying to use EKF packages (i.e., robot_pose_ekf or robot_localization) to fuse odometry and IMU in the HSR from Toyota Research Institute. When I first tried to hook the robot_pose_ekf package with my mobile robot, I encountered this following error:
[ERROR] [1519539033.564366334]: Covariance specified for measurement on topic wheelodom is zero
[ERROR] [1519539036.363531683]: filter time older than odom message buffer
....
So I checked the published data from the odometry (nav_msgs/Odometry) and IMU (sensor_msgs/Imu), and the covariance matrices in those are indeed all 0.
I am confused since I don't know whether it is common to have 0 covariances from those published data and we need to characterize and estimate those sensor noise covariances by collecting bunch of data with trials and errors (I don't have any sensor specification though)....?
Originally posted by kidpaul on ROS Answers with karma: 38 on 2021-10-04
Post score: 0