Monitoring Electrostatic Adhesion Forces via Acoustic Pressure

TL;DR

This paper introduces a low-cost, non-contact acoustic-pressure-based method for monitoring electrostatic adhesion forces, enabling mass estimation and system monitoring without bulky sensors in robotic applications.

Contribution

The study presents a novel acoustic pressure sensing technique to monitor EA forces and object mass, reducing system complexity and enabling multi-object and real-time monitoring.

Findings

Acoustic pressure peaks correlate with object mass and contact area.

The method successfully estimates object mass and monitors multiple EA systems.

Integration into an end effector allows real-time mass change detection during transport.

Abstract

Electrostatic adhesion is widely used in mobile robotics, haptics, and robotic end effectors for its adaptability to diverse substrates and low energy consumption. Force sensing is important for feedback control, interaction, and monitoring in the EA system. However, EA force monitoring often relies on bulky and expensive sensors, increasing the complexity and weight of the entire system. This paper presents an acoustic-pressure-based method to monitor EA forces without contacting the adhesion pad. When the EA pad is driven by a bipolar square-wave voltage to adhere a conductive object, periodic acoustic pulses arise from the EA system. We employed a microphone to capture these acoustic pressure signals and investigate the influence of peak pressure values. Results show that the peak value of acoustic pressure increased with the mass and contact area of the adhered object, as well as with the amplitude and frequency of the driving voltage. We applied this technique to mass estimation of various objects and simultaneous monitoring of two EA systems. Then, we integrated this technique into an EA end effector that enables monitoring the change of adhered object mass during transport. The proposed technique offers a low-cost, non-contact, and multi-object monitoring solution for EA end effectors in handling tasks.