Normal Direction Measurement and Optimization With a Dense Three-Dimensional Point Cloud in Robotic Drilling

作者：Rao, Gang; Wang, Guolei; Yang, Xiangdong; Xu, Jing^*; Chen, Ken

来源：IEEE/ASME Transactions on Mechatronics, 2018, 23(3): 986-996.

DOI：10.1109/TMECH.2017.2747133

• Surface smoothness
• tensor voting
• three-dimensional (3-D) point cloud

In large-scale structure assembly, the normal direction of a drilled surface is required to be measured online instead of extracted directly from the computer-aided design model because of tool error, cutting force, and other factors. To this end, first, a high-resolution structured-lightbased three-dimensional (3-D) measurement is adopted to improve measurement reliability; second, tensor voting is proposed to remove noise and fill in blanks in the measured 3-D point cloud to obtain a uniform point distribution for surface fitting; and third, the surface smoothness after rivet installation is defined and optimized. The proposed methods are verified by simulations and experiments. The results show that the proposed methods are effective.

• 出版日期2018-6
• 单位清华大学