Pose Estimation of Magnetically Driven Helical Robots With Eye-in-Hand Magnetic Sensing

Abstract

This letter presents a magnetic-based pose sensing method for magnetically driven helical robots. Unlike conventional methods that directly compute pose from magnetic field measurements, the proposed approach decouples magnetic field components caused by the helical robot's pose from the rotating magnetic field by deriving the analytic relationship between the spatial characteristics of the rotating magnetic field and the rotating permanent magnet (PM). A magnetic field model for a dual-rotating PM system is established under quasi-static driving conditions, enabling real-time pose estimation by taking account into the effects of the driving PM. To address workspace and signal quality limitations, a mobile sensor array in eye-in-hand configuration is presented, achieving follow-up measurements with improved signal-to-noise ratio and high precision. The proposed method has been validated experimentally on a magnetically driving platform and the results demonstrate that this method enables large-range tracking with limited number of sensors and provides a robust solution for continuous real-time pose sensing for in magnetically driven helical robots.