scholarly journals Online IMU Self-Calibration for Visual-Inertial Systems

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1624 ◽  
Author(s):  
Yao Xiao ◽  
Xiaogang Ruan ◽  
Jie Chai ◽  
Xiaoping Zhang ◽  
Xiaoqing Zhu
Keyword(s):  
Inertial Sensor ◽  
Low Cost ◽  
Optimization Methods ◽  
Calibration Method ◽  
Measurement Unit ◽  
Intrinsic Parameters ◽  
Self Calibration ◽  
Calibration Problem ◽  
System States ◽  
Inertial Systems

Low-cost microelectro mechanical systems (MEMS)-based inertial measurement unit (IMU) measurements are usually affected by inaccurate scale factors, axis misalignments, and g-sensitivity errors. These errors may significantly influence the performance of visual-inertial methods. In this paper, we propose an online IMU self-calibration method for visual-inertial systems equipped with a low-cost inertial sensor. The goal of our method is to concurrently perform 3D pose estimation and online IMU calibration based on optimization methods in unknown environments without any external equipment. To achieve this goal, we firstly develop a novel preintegration method that can handle the IMU intrinsic parameters error propagation. Then, we frame IMU calibration problem into general factors so that we can easily integrate the factors into the current graph-based visual-inertial frameworks and jointly optimize the IMU intrinsic parameters as well as the system states in a big bundle. We evaluate the proposed method with a publicly available dataset. Experimental results verify that the proposed approach is able to accurately calibrate all the considered parameters in real time, leading to significant improvement of estimation precision of visual-inertial system (VINS) compared with the estimation results with offline precalibrated IMU measurements.

scholarly journals Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment

2019 ◽  
Vol 11 (4) ◽  
pp. 442 ◽  
Author(s):  
Zhen Li ◽  
Junxiang Tan ◽  
Hua Liu
Keyword(s):  
Inertial Measurement Unit ◽  
Point Clouds ◽  
Calibration Method ◽  
Satellite System ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Self Calibration ◽  
Global Navigation Satellite ◽  
Mean Square Errors ◽  
Scanning Systems

Mobile LiDAR Scanning (MLS) systems and UAV LiDAR Scanning (ULS) systems equipped with precise Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) positioning units and LiDAR sensors are used at an increasing rate for the acquisition of high density and high accuracy point clouds because of their safety and efficiency. Without careful calibration of the boresight angles of the MLS systems and ULS systems, the accuracy of data acquired would degrade severely. This paper proposes an automatic boresight self-calibration method for the MLS systems and ULS systems using acquired multi-strip point clouds. The boresight angles of MLS systems and ULS systems are expressed in the direct geo-referencing equation and corrected by minimizing the misalignments between points scanned from different directions and different strips. Two datasets scanned by MLS systems and two datasets scanned by ULS systems were used to verify the proposed boresight calibration method. The experimental results show that the root mean square errors (RMSE) of misalignments between point correspondences of the four datasets after boresight calibration are 2.1 cm, 3.4 cm, 5.4 cm, and 6.1 cm, respectively, which are reduced by 59.6%, 75.4%, 78.0%, and 94.8% compared with those before boresight calibration.

A self-calibration method for non-orthogonal angles of gimbals in rotational inertial navigation system based on fiber optic gyro

2017 ◽  
Vol 40 (13) ◽  
pp. 3665-3674 ◽  
Author(s):  
Zengjun Liu ◽  
Lei Wang ◽  
Wei Wang ◽  
Tianxiao Song
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Fiber Optic ◽  
Inertial Navigation ◽  
Calibration Method ◽  
Measurement Unit ◽  
Fiber Optic Gyroscope ◽  
Self Calibration ◽  
Photoelectric Encoder ◽  
Navigation Accuracy

Rotating modulation technique is a mature method that has been widely used in the rotational inertial navigation system (RINS). Tri-axis RINS has three gimbals, and the Inertial Measurement Unit can rotate along three directions to modulate the inertial devices’ errors, so that the navigation accuracy of the system can be greatly improved. However, the outputs of attitudes are easily affected by the non-orthogonal angles of gimbals, which should be accurately calibrated and compensated. In this paper, the effects of the non-orthogonal angles on the attitudes are discussed detailed and simulations based on Matlab are conducted to verify that firstly; then, a self-calibration method based on the outputs of the fiber optic gyroscope and photoelectric encoder is proposed. Experimental results in a real tri-axis RINS show that the attitude outputs accuracy are improved from 150” to less than 10”, which verify the practicability of the calibration method proposed in this paper.

A self-calibration method with high-accuracy and low-cost for large-area motion stage based on digital grating projection mode

2019 ◽  
Vol 12 (12) ◽  
pp. 126503
Author(s):  
Shengzhou Huang ◽  
Mujun Li ◽  
Lei Wang ◽  
Yongsheng Su ◽  
Yi Liang
Keyword(s):  
Low Cost ◽  
Calibration Method ◽  
High Accuracy ◽  
Large Area ◽  
Self Calibration ◽  
Motion Stage

scholarly journals Estimation of 3D Knee Joint Angles during Cycling Using Inertial Sensors: Accuracy of a Novel Sensor-to-Segment Calibration Procedure Based on Pedaling Motion

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2474 ◽  
Author(s):  
Sébastien Cordillet ◽  
Nicolas Bideau ◽  
Benoit Bideau ◽  
Guillaume Nicolas
Keyword(s):  
Knee Joint ◽  
Inertial Sensor ◽  
External Rotation ◽  
Calibration Method ◽  
Calibration Procedure ◽  
Angle Measurement ◽  
Measurement Unit ◽  
Joint Angles ◽  
Calibration Methods ◽  
Flexion Extension

This paper presents a novel sensor-to-segment calibration procedure for inertial sensor-based knee joint kinematics analysis during cycling. This procedure was designed to be feasible in-field, autonomously, and without any external operator or device. It combines a static standing up posture and a pedaling task. The main goal of this study was to assess the accuracy of the new sensor-to-segment calibration method (denoted as the ‘cycling’ method) by calculating errors in terms of body-segment orientations and 3D knee joint angles using inertial measurement unit (IMU)-based and optoelectronic-based motion capture. To do so, 14 participants were evaluated during pedaling motion at a workload of 100 W, which enabled comparisons of the cycling method with conventional calibration methods commonly employed in gait analysis. The accuracy of the cycling method was comparable to that of other methods concerning the knee flexion/extension angle, and did not exceed 3.8°. However, the cycling method presented the smallest errors for knee internal/external rotation (6.65 ± 1.94°) and abduction/adduction (5.92 ± 2.85°). This study demonstrated that a calibration method based on the completion of a pedaling task combined with a standing posture significantly improved the accuracy of 3D knee joint angle measurement when applied to cycling analysis.

scholarly journals Self-Calibration of an Industrial Robot Using a Novel Affordable 3D Measuring Device

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3380 ◽  
Author(s):  
Martin Gaudreault ◽  
Ahmed Joubair ◽  
Ilian Bonev
Keyword(s):  
Industrial Robot ◽  
Low Cost ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Geometrical Parameters ◽  
Robot Arm ◽  
Measuring Device ◽  
Self Calibration ◽  
Position Errors

This work shows the feasibility of calibrating an industrial robot arm through an automated procedure using a new, low-cost, wireless measuring device mounted on the robot’s flange. The device consists of three digital indicators that are fixed orthogonally to each other on an aluminum support. Each indicator has a measuring accuracy of 3 µm. The measuring instrument uses a kinematic coupling platform which allows for the definition of an accurate and repeatable tool center point (TCP). The idea behind the calibration method is for the robot to bring automatically this TCP to three precisely-known positions (the centers of three precision balls fixed with respect to the robot’s base) and with different orientations of the robot’s end-effector. The self-calibration method was tested on a small six-axis industrial robot, the ABB IRB 120 (Vasteras, Sweden). The robot was modeled by including all its geometrical parameters and the compliance of its joints. The parameters of the model were identified using linear regression with the least-square method. Finally, the performance of the calibration was validated with a laser tracker. This validation showed that the mean and the maximum absolute position errors were reduced from 2.628 mm and 6.282 mm to 0.208 mm and 0.482 mm, respectively.

Simultaneous Calibration for MEMS Gyroscopes of the Rocket IMU

2014 ◽  
Vol 896 ◽  
pp. 656-659 ◽  
Author(s):  
Wahyudi ◽  
Adhi Susanto ◽  
Wahyu Widada ◽  
Sasongko P. Hadi
Keyword(s):  
Low Cost ◽  
Angular Rate ◽  
Calibration Method ◽  
Sensor Technology ◽  
Measurement Unit ◽  
Angular Rate Sensor ◽  
Motion Simulator ◽  
Wide Range ◽  
Mems Gyroscopes ◽  
Mean Square Errors

MEMS (Microelectromechanical System), as an advanced sensor technology, is low power, low cost, and small size. Gyroscope sensor produced with microelectromechanical technology is an angular rate sensor. IMU (Inertial Measurement Unit) sensor for rocket should have a very wide range of measurements. At the beginning of the motion, the rocket accelereation is very high, for which the rocket IMU requires a multisensor with different sensitivity. This paper presents the design of the rocket IMU and its calibration method for all MEMS gyroscopes. Calibration for each sensor is necessary including its varying characteristics. The calibration of the gyroscope sensors use three-axis motion simulator model ST 3176 with resolutions 0.00001 for all axes. Simultaneous calibration was mutually applied which require a short calibration time. The results show that root mean square errors (RMSE) of the calibrated gyroscope for all axes are under 2.5 %. Therefore, that the calibrated gyroscope can be used in the proposed real application.

Wireless Input Technology Based on MEMS Inertial Measurement Unit - A Survey

2017 ◽  
Vol 870 ◽  
pp. 79-84
Author(s):  
Zhen Xian Fu ◽  
Guang Ying Zhang ◽  
Yu Rong Lin ◽  
Yang Liu
Keyword(s):  
Inertial Measurement Unit ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Cost ◽  
Propagation Model ◽  
Measurement Unit ◽  
Input Device ◽  
Operational Environment ◽  
Inertial Measurement ◽  
Mems Imu

Rapid progress in Micro-Electromechanical System (MEMS) technique is making inertial sensors increasingly miniaturized, enabling it to be widely applied in people’s everyday life. Recent years, research and development of wireless input device based on MEMS inertial measurement unit (IMU) is receiving more and more attention. In this paper, a survey is made of the recent research on inertial pens based on MEMS-IMU. First, the advantage of IMU-based input is discussed, with comparison with other types of input systems. Then, based on the operation of an inertial pen, which can be roughly divided into four stages: motion sensing, error containment, feature extraction and recognition, various approaches employed to address the challenges facing each stage are introduced. Finally, while discussing the future prospect of the IMU-based input systems, it is suggested that the methods of autonomous and portable calibration of inertial sensor errors be further explored. The low-cost feature of an inertial pen makes it desirable that its calibration be carried out independently, rapidly, and portably. Meanwhile, some unique features of the operational environment of an inertial pen make it possible to simplify its error propagation model and expedite its calibration, making the technique more practically viable.

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