# from RGBD to 2d grid_map for path planning

Hi, i have a problem obtaining a 2D occupancy grid (which i need for path planning algorithm) given an RGBD image. I've read about costmap_2d for obtaining a costmap given a pointcloud, or depthimage_to_laserscan that can give me a laser-like perception starting from a depth image, but i want to know if there is some library which i can rely on for my purpose and maybe a function that can do what i need in optimized way. I can use both c++ and python. I'm sorry I cannot give the url of the code, i only know the assignment of building a 2D occupancy grid starting form info given by and RGBD camera. Thanks for the help

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Please provide more background info. Are you starting from an existing demo? If so, please provide url. Are you using move_base? Do you intend to use c++ or python? You can edit your existing description using the "edit" button at the end of the text.

( 2021-11-29 08:02:04 -0600 )edit

Thanks for the suggestions, i've modified the question.

( 2021-11-29 15:47:54 -0600 )edit

I also don't know what you're supposed to do. This is a relatively simple computation to perform if the image data and the costmap are in the same reference frame. No, I don't know of any library that does exactly this operation.

You posted this question on a ros site. ros can do this, but this operation is only a tiny, tiny piece of what the move_base package does. You will have to climb a very big learning curve just to solve a simple math calculation (assuming that you are not already familiar with ros.) With what you've told us above, taking the ros path for this is just not an efficient use of your time.

( 2021-11-30 20:14:56 -0600 )edit