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can not track small dynamic obstacles when using a single-line laser #41
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Hi @UyaSong , You can also increase the number of clusters so that you can have more objects detected and tracked which will likely include the (smaller) human-leg point clouds. |
Hi @praveen-palanisamy , |
It's been quite some time since then that I am not able to recall all the details but the implementation was using PCL. Specifically the pcl_filters (pcl_segmentation also is useful for filtering background planes). There's a tutorial demonstrating the use of the I hope that helps you filter the (static/baground/noisy) point clouds. |
Thanks a lot! I will have a try. |
hello,I have some questions in Point cloud topic release and acceptance,Can you add me? Pay for some advice,qq:2335702163 |
Hi @mshmsh1512987 , you can refer to below link for point cloud topic subscribe and publish. It works well. @mshmsh1512987 |
@UyaSong Hi, I have a similar use case. Did you figure out how to efficiently filter the scans for use with this package? |
I have developed a filter which improves the package in case a prior static map is given: |
Hi @praveen-palanisamy , thanks for sharing your work, it's quite helpful to me.
I want to run this pkg on a mobile robot with a single-line laser, but it can hardly detect the dynamic obstacle (human legs), like the video shows.
I don't know whether I had used it correctly. Maybe I should increase the number of cluster and kalman filter. Or should I use the featureDetection class?
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