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I've had some success doing this by using PointCloud Library's built-in functions, namely Statistical Outlier Removal. It really depends where the majority of your points lie. If there's a lot of grass, this won't work as well. If the grass is sparse, this method could definitely improve your performance. Radial Outlier Removal might also work.
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I've had some success doing this by using PointCloud Library's built-in functions, namely Statistical Outlier Removal. It really depends where the majority of your points lie. If there's a lot of grass, this won't work as well. If the grass is sparse, this method could definitely improve your performance. Radial Outlier Removal might also work.
EDIT:
In order to get a ROS sensor_msgs/PointCloud2 to a pcl cloud, use the following code:
sensor_msgs::PointCloud2 cloud_in;
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
pcl::fromROSMsg(cloud_in, *cloud);
The cloud variable will now contain a pcl cloud that you can use with the PCL built-in functions.
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