Signal processing of capacitive force sensors installed in the foot of an anthropomorphic robot

Abstract

Introduction: The force-moment sensing of the functional surfaces in robots based on compact capacitive force sensors can significantly improve interaction with the environment and humans. Capacitive force sensors provide high measurement accuracy and speed, but the electromagnetic interference can affect significantly the signal. When processing signals the influence of external noise must be taken into account, which increases the computation time. Purpose: To apply the developed interface circuit for processing signals from capacitive primary force transducers in a real-world robot. Results: Experimental verification of the developed solutions implied simulation of a step of the pedipulator of an anthropomorphic robot with the calculation of the coordinates of the center of pressure exerted on the foot with the four installed capacitive sensors. Software filtering and measuring capabilities of the microcontroller made it possible to achieve a signal-to-noise ratio of approximately 62.24 dB, which allows a closed-loop control system to function correctly. The average time for calculating the coordinates of the center of pressure on the foot with software filtering of the signal on the on-board computer of the robot was from 3.1 to 6.1 ms and meets the requirements for the sensory system of a walking robot. Practical relevance: The interface circuit allows to scale the number of connected primary force transducers, while software processing allows to normalize transducer signals by applying the calculated correction factors. Proposed solutions can be used in different robotic systems for real-time force measurement.