Math & Kinematics

Wavelet Transform

The wavelet transform is a signal-processing technique that decomposes a signal into components localized in both time and frequency using scaled and shifted copies of a basis wavelet, unlike the Fourier transform, which localizes only in frequency. In robotics it is applied to vibration and fault analysis, tactile and force signal processing, and multiresolution image and terrain analysis.

Why it matters for physical AI

Contact events, slips, and mechanical faults are transient signals buried in noisy sensor streams, and time-frequency decompositions remain effective features for detecting them in real time on resource-limited hardware.