The calibration device and method of humanoid finger sensor based on multimodal perception

Depending on a humanoid finger sensor with multimodal perception capability, physical properties such as pressure, temperature, texture features, surface roughness, micro vibration, etc., could be easily extracted when the sensor contacts with different objects. In this paper, an innovative calibration device is created, as well as the motor controllers, centre control system, hardware and software system. The Least Square method is proposed for data fitting and parameter predicting, which is used to implement precise calibration for pressure and its distribution. The Frequency Spectrum Analysis method is presented by using Fast Fourier Transform to determine different physical properties of objects under certain frequency range and energy distribution. With the analysis of calibration data and results, the contact force and temperature range are obtained in good linearity, meanwhile the method for how to distinguish objects with similar texture features is put forward by using the Frequency Spectrum Analysis. This study provides a set of systematic calibration methods for the humanoid robot fingers, which can be served as an efficient reference to perceive multimodal objects.