Final Thoughts and Tips

We hope that the template script and this guide will help make debugging lidar data and creating tasks a smoother process. Here are some more tips that may help.

See also

Remember to check the object Transform from scale_lidar_io, this will help you with all the algebraic operation (matrix multiplication, subtraction, etc.). Also you can create a Transform object using different type of data, not only matrixes. Transforms prints translate your matrixes into simple components to help you understand your data.

Extra tips

Subtracting a matrix from another matrix:

matrix_one = Transform(np.eye(4))
matrix_two = Transform(numpy.indices((4, 4)))

print(matrix_one @ matrix_two.inverse)

See also

Remember that the order of the element matters in matrix multiplication, it is not the same

The lidar toolkit’s expected input format

The lidar toolkit expects data in a specific format to construct the output json. If something errors out or does not make sense, remember to check how the lidar toolkit operates. There is the chance that a pose was applied twice, or the raw data was using a quaternion and the lidar toolkit was expecting a rotation matrix.

My Data Still Looks Bad

In the section Lidar toolkit In depth / Troubleshooting your data we have more cases of how to debug and load your data into the lidar toolkit. When in doubt, reach out to your Scale Engagement Manager.