wheel encoders, robot_localization and robot_pose_ekf
Hey!
I'm just testing out the robot_localization package with our robots. Loving the level of documentation :). However, I realized that it handles the data streams differently from robot_pose_ekf. For instance, robot_pose_ekf, expected wheel odometry to produce position data that it then applied differentially i.e. it took the position estimate at t_k-1 and t_k, transformed the difference to the odom frame, and applied it to the state estimate.
However as per the discussion about yaw velocities here, it seems robot_localization would rather just apply wheel velocities generated by the wheel odometry and generate a position information itself. I know robot_localization has a "differential" tag on each dataset but that seems to be removing initial static offsets (i.e. subtract the position estimate at t_0 , not t_k-1). I have two questions:
- Are my assumptions above correct?
- Am I losing anything by not doing the integration myself and relying on robot_localization to do the integration?
