Evaluation of attitude estimation algorithms using absolute magnetic reference data: Methodology and results

Abstract

Location is a growing problem due, for instance, to the expansion of civil drones or intelligent vehicles. This expansion was made possible through the development of microelectromecanical systems (MEMS), cheap and miniaturized inertial sensors. In this context, this article is devoted to the development of a simulator which generates the sensor measurements, giving a specific trajectory, in order to validate and compare pose estimation algorithms. After validation of the simulator with real movements and measurements, four pose estimation algorithms from the literature are compared on different trajectories. All these algorithms use magnetic field sensors in addition of the classical inertial sensors. This comparison is led to select an algorithm for a future application with multiple IMUs.

Magnetometer-Augmented IMU Simulator: In-Depth Elaboration

“…The objective is also to simulate any kind of trajectory: short vs. long, high vs. low dynamics, etc. This section competes a description provided in a previous paper by the present authors [ 11 ].…”

“…This paper shows a more accurate and complete validation of a magnetometer-augmented IMU simulator than the previously cited papers. It consists of placing an IMU in a three-axis table, which has been developed at ISL (French-German Research Institute of Saint-Louis)[ 11 ]. The absolute encoders of the electric engines are used to measure the 3D motion of the table.…”

Quaternion-based IMU and stochastic error modeling for intelligent vehicles

“…Indeed, quaternions do not suffer from the angle singularities known as the gimbal lock problem. The sensor data simulator has already been validated with real measurements considering low dynamics [7], [8]. In this paper, a validation is proposed in the intelligent vehicles context using low and high dynamics issued from real trials.…”