Robotiz3D and Desupervised have got a RIMA
grant to bring this to life. At Desupervised we’re focusing on analyzing the 3D point clouds to identify the various defects, using a combination of AI modeling techniques.
Since we got involved in the project at a very early stage, before the sensor equipment was actually ready, we started our work with synthetic data where we evaluated several point cloud model architectures for their suitability. We first landed on the PointNet++ architecture before finally transitioning to an architecture named RandLA-Net.