Frequency-aware decomposition learning for sensorless wrench estimation in vibration-rich robotic contact
The Frequency-aware Decomposition Network (FDN) forecasts vibration-rich wrench by decomposing it into a trend and residual component using spectral methods. It uses frequency-aware filters to adaptively enhance input data and imposes frequency band priors on the outputs, specifically modeling high-frequency components like those from grinding.