A two-step machining and active learning approach for right-first-time robotic countersinking through in-process error compensation and prediction of depth of cuts.
Robotics Comput. Integr. Manuf., 2022
A perturbation signal based data-driven Gaussian process regression model for in-process part quality prediction in robotic countersinking operations.
Robotics Comput. Integr. Manuf., 2021