A new method for online chatter detection and suppression in robotic milling is presented. To compute the chatter stability of robotic milling along a curvilinear tool path characterized by significant variation in robot arm configuration and cutting conditions, the tool path is partitioned into small sections such that the dynamic stability characteristics of the robot can be assumed to be constant within each section. A methodology to determine the appropriate section length is proposed. The instantaneous cutting force-induced dynamic strain signal is measured using a wireless piezoelectric thin-film polymer (polyvinyldene fluoride (PVDF))-based sensor system, and a discrete wavelet transform (DWT)-based online chatter detection algorithm and chatter suppression strategy are developed and experimentally evaluated. The proposed chatter detection algorithm is shown to be capable of recognizing the onset of chatter while the chatter suppression strategy is found to be effective in minimizing chatter during robotic milling.

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