Sensing and control for automated robotic edge deburring

The authors describe the sensing and control elements of a system for automated robotic edge deburring. The deburring path, automatically generated by a task planner, is corrected online by an active end effector with the objective of controlling the chamfer depth. The sensing system combines the information from force and vision sensors during deburring to provide an improved depth measurement. The vision sensor is then used to verify the deburring performance in an inspection pass. The control system incorporates adaptive predictive control combined with learning control. The system was tested through computer simulations, and deburring experiments performed on one and two-dimensional edges.<>