An approach for precise CAD reconstruction based on TEASER++, iterative ICP methods for robotics applications

This paper outlines a systematic approach to improve the precision of 3D reconstructions from blurry point cloud images taken by a 3D camera. The process involves thorough 3D scanning, point cloud image alignment and precise 3D robotic pose estimation. Global registration utilizes TEASER++, and local registration employs the Iterative Closest Point algorithm for rotation and translation estimation. The alignment results are utilized to generate an enhanced CAD model. An accurate 3D robotic pose is determined from the CAD model data. Validation is done using LEGO components, benchmarked against an industrial tool for performance evaluation.