# Revision history [back]

How does the dwa_local_planner know about the rotation axis length of the robot? Is it from the footprint?

DWA does not explicitly model the rotation axis length. It assumes the rotation happens relative to /base_footprint and uses the footprint to figure out how much space the robot takes up.

My footprint is a simplified almost rectangular bounding box of the robot. Does it make a difference If I make it precise enough to exactly match the footprint of the robot?

It's not likely that the precision will make a difference unless the footprint is a bad approximation.

Is the Cost value example in the dwa_local_planner webpage that is calculated from the goal_distance , path_distance and occdist values a positive (the high the better path) or negative value? On top of the page it talks about a scoring trajectory but below the example is cost, so I am a bit confused.

Yes, the language is not clear. It is calculated in terms of costs, not positive scores. It minimizes the sum of the costs.

Do you know why the robot fails while there is a clear solution available?

How does the dwa_local_planner know about the rotation axis length of the robot? Is it from the footprint?

DWA does not explicitly model the rotation axis length. It assumes the rotation happens relative to /base_footprint and uses the footprint to figure out how much space the robot takes up.

My footprint is a simplified almost rectangular bounding box of the robot. Does it make a difference If I make it precise enough to exactly match the footprint of the robot?

It's not likely that the precision will make a difference unless the footprint is a bad approximation.

Is the Cost value example in the dwa_local_planner webpage that is calculated from the goal_distance , path_distance and occdist values a positive (the high the better path) or negative value? On top of the page it talks about a scoring trajectory but below the example is cost, so I am a bit confused.

Yes, the language is not clear. It is calculated in terms of costs, not positive scores. It minimizes the sum of the costs.

Do you know why the robot fails while there is a clear solution available?

One bit is that your inflation radius is too small. It should be at least half the width of your robot (.28)