This week’s work was still centered on the development of a tool to preform a quantitative evaluation of the method developed. This proved to be a bigger challenge than anticipated, yet, the more plausible solution seems to remain in the conversion of a line drawn in google earth to an occupancy grid. The data on this grid, corresponding to the road limits ground truth, will then be compared to the data on the detected limits grids and statistical measures can be evaluated.
At this point, the program is able to generate .kml files with the path traveled, read .kml files produced by google earth features, extract the coordinates and calculate its distance to the car coordinates.
However, this fails on the correct orientation of frames, considering that the world frame where the latitude and longitude are oriented is not aligned to the moving_axis frame, making the ground truth limits unaligned and in the wrong orientation.
To correct this problem, a possible solution is to insert the points in a new point cloud (with z=0) and use pcl_ros::transformPointCloud to transform the points within frames (wgs84 to moving_axis). This would return a new point cloud with the necessary corrections to align the frames, that would allow to correctly place the points in the occupancy grid.