estimated pose by hector mapping and robot_pose_ekf
Hello
Im using three methods for my robot localisation and needs some helps regarding the estimated pose and the outcomes of those methods. First I tried AMCL and hector Mapping. There is significant improvements of the estimated pose by the Hector Mapping as the scan matching make a better performance. Than I tried the robot_pose_ekf package. First I fuse IMU and the virtual odometry from Hector Mapping. My virtual odometry contains also velocity massages. So the estimates pose from robot_pose_ekf almost does not differs from the Hector Mapping ones. When I used robot_pose_ekf fusing IMU with a real odometry from my wheel encoders the estimated pose follows the odometry but still is not so good as the from Hector Mapping. The odometry coming from the encoders also contains velocity. So is there any explonation about my results. And also when I extracted the velocity profiles (linear and angular velocity) of the robot runs there is almost no difference in all 4 methods.
Any help?
