Dipole Model-Based Magnetic Disturbance Compensation Method for Mobile Robots Using a Magnetometer Array

Vector magnetometers are widely used in mobile robot applications as compasses based on the Earth's magnetic field. These sensors are largely affected by objects that influence the magnetic field, which leads to unreliable measurements. In this paper, a new method is proposed for the compensation of disturbances caused by nearby objects. The method applies measurements of a technology for object detection and a magnetic sensor array, which are both installed on the mobile robot. The object detection sensor is utilized to provide the position of the detected objects in the robot's coordinate frame. The objects are assumed to have a dipole-like disturbance. The measurements of the magnetic sensor array are utilized to estimate the dipole parameters using genetic algorithm-based optimization. The compensated measurements can be computed by subtracting the estimated disturbances from the original measurements. The method is validated using simulations made with various setups based on different numbers of both magnetic sensors and detected objects. The obtained results show that the dipole parameters can be efficiently estimated if the number of sensors is higher than the number of objects. The method can also distinguish if a detected object does not influence the magnetic field. It is shown that the computed disturbances can be efficiently used for compensation.