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Deeper control over robot self-filtering

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Good day, For an application, we are developing it is important to use the self-filtering feature from Moveit package, but there are quite a few things that we need to either further develop or be able to control. First, currently Moveit! only allows starting self-filtering with the sensor_pluging occupancy_map_monitor/PointCloudOctomapUpdater but in our case, we **only want to use the self-filtering** function (collision avoidance is handled differently). Furthermore, **the output of the self-filter function stores only the x,y,z channels of the input cloud. In our case, normals and curvature information are important for the next stage of processing**, which in theory we want to perform with the self-filtered cloud; meaning that, we either need a cloud with the original channels minus the robot points, or the points "masks" indicating which of them are part of the robot. I have seen the [robot_self_filter](http://wiki.ros.org/robot_self_filter) package and its [documentation](https://docs.ros.org/diamondback/api/robot_self_filter/html/index.html) but this looks rather outdated, and since there is no use of this package in the current moveit code, I assume this is not the package to use. My question would be, **which are the packages and scripts used by Moveit for its self-filtering functions (I understand this function is not stable or in beta), is there any documentation on only self-filtering?.** I am interested in updating this function to include the functionalities mentioned above and maybe try to include some more, and document it.

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