ROS Robot_Localization Functionality
Hi there,
I recently started working with the ROS robot_localization package and wanted to enquire about a few unknowns about the package. If you could please provide some insight as to these unknowns I would be greatly appreciative.
How does the package handle multiple sensors of the same type (10 IMUs for instance) if one of the sensors is publishing a grossly erroneous value compared to the other sensors? Does it do some form of weighted averaging or is there some built in statistical analysis that assesses the data and detects outliers? I saw there was the differential feature to resolve this issue but are there any other systems in place to resolve this issue.
Is there a diagram of the control functionality for the EKF? I'm looking to understand how the EKF integrates/ differentiates sensory data to eventually achieve a dead reckoning estimate.
Does the package generate data points from sensors that do not necessarily possess the required information? What I mean by this is, if you have a velocity sensor, do you derive its value to achieve an acceleration estimate to assist in EKF comparison between sensors or is it all flowing downward from a highest order down to a position estimate? My thinking is that if I have a position sensor and an acceleration sensor, would you derive position data to achieve another acceleration estimate to help the acceleration sensor determine any outliers, etc.
Any and all insight with respect to the aforementioned questions would be greatly appreciated.