Inertial Sensor Self-Calibration in a Visually-Aided Navigation Approach for a Micro-AUV

Sensors

Francisco Bonin-Font¹  Miquel Massot-Campos¹  Pep Lluis Negre-Carrasco¹  Gabriel Oliver-Codina¹ 

[1] Systems, Robotics and Vision, Department of Mathematics and Computer Science, University of the Balearic Islands, Cra de Valldemossa, km 7.5, Palma de Mallorca 07122, Spain; E-Mails:

关键词: sensor fusion;    visual localization;    autonomous underwater vehicles;    underwater landscape;   

DOI  :  10.3390/s150101825

来源: mdpi

【 摘 要 】

This paper presents a new solution for underwater observation, image recording, mapping and 3D reconstruction in shallow waters. The platform, designed as a research and testing tool, is based on a small underwater robot equipped with a MEMS-based IMU, two stereo cameras and a pressure sensor. The data given by the sensors are fused, adjusted and corrected in a multiplicative error state Kalman filter (MESKF), which returns a single vector with the pose and twist of the vehicle and the biases of the inertial sensors (the accelerometer and the gyroscope). The inclusion of these biases in the state vector permits their self-calibration and stabilization, improving the estimates of the robot orientation. Experiments in controlled underwater scenarios and in the sea have demonstrated a satisfactory performance and the capacity of the vehicle to operate in real environments and in real time.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.