kalman_filter_localization
kalman_filter_localization copied to clipboard
rsasaki0109
Validate fusion result
Hii, I've one more question: How to validate the accuracy of the fusion result?
The accuracy cannot be verified with sample data. You can verify the accuracy of this ekf by using it with an open data set with true values, such as KITTI.
Excuse me, I don't use GPS, I only use Odom. Why is the output topic messy and the data floating? When GPS and Odom are input at the same time, which is used for observation?
Sorry, the debugging of the Odom complex may have been poor. I'll fix it as soon as I figure out the problem.
Excuse me, I don't use GPS, I only use Odom. Why is the output topic messy and the data floating? When GPS and Odom are input at the same time, which is used for observation?
As far as I know, any type of odometry (wheel odom, visual odom, visual-inertial odom... etc. ) suffers from drift. Fundamentally, there is no way we can correct them without a bounded correction source (e.g. GPS, wifi Beacon, Place Recognition(in case of SLAM)... etc). In order to make odometry in novel EKF, the code needs an extra code bit for odometry prediction.
Meanwhile, in kalman_filter_localization package, both odom and GPS are used as observation. Odom has a relatively small drift to IMU, the assumption is reasonable for local navigation. However, the pose will keep drifting out from the gound truth as it uses poorly estimated covariance updates.
There might be a wrong explanation, so feel free to make a comment to correct this posting
