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Gmapping in a complex environment.

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I am using a turtlebot2 with an ASUS XTION laser scanner and I am trying to develop autonomous mapping functionality but I am running into a lot of issues with path planning. The robot often gets stuck and is unable to find a path to its goal. I am currently testing in an office environment that has a lot of complex obstacle features (chair legs, table legs, human legs, etc.) and I was wondering if these features might be affecting the performance of the path planner? There are also a few ceiling-to-floor windows which may be confusing the laser scanner. Does anyone know the limitations of the DWA local planner in complex environments? In videos I see online, people often create very structured maze like environments which make it easy for the robot to navigate. Otherwise, I'll need to tweak some parameters...

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