On the calibration aspects of MEMS-IMUs used in micro UAVs for sensor orientation

2020 ◽  
Author(s):  
Philipp Clausen ◽  
Jan Skaloud
Keyword(s):  
Sensor Orientation

scholarly journals Surface-Parallel Sensor Orientation for Assessing Energy Balance Components on Mountain Slopes

2015 ◽  
Vol 158 (3) ◽  
pp. 489-499 ◽  
Author(s):  
P. Serrano-Ortiz ◽  
E. P. Sánchez-Cañete ◽  
F. J. Olmo ◽  
S. Metzger ◽  
O. Pérez-Priego ◽  
...  
Keyword(s):  
Energy Balance ◽  
Sensor Orientation

scholarly journals Novel MARG-Sensor Orientation Estimation Algorithm Using Fast Kalman Filter

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Siwen Guo ◽  
Jin Wu ◽  
Zuocai Wang ◽  
Jide Qian
Keyword(s):  
Kalman Filter ◽  
Process Model ◽  
Attitude Determination ◽  
Angular Rate ◽  
Estimation Algorithm ◽  
Measurement Model ◽  
Estimation Accuracy ◽  
Orientation Estimation ◽  
Kinematic Equation ◽  
Sensor Orientation

Orientation estimation from magnetic, angular rate, and gravity (MARG) sensor array is a key problem in mechatronic-related applications. This paper proposes a new method in which a quaternion-based Kalman filter scheme is designed. The quaternion kinematic equation is employed as the process model. With our previous contributions, we establish the measurement model of attitude quaternion from accelerometer and magnetometer, which is later proved to be the fastest (computationally) one among representative attitude determination algorithms of such sensor combination. Variance analysis is later given enabling the optimal updating of the proposed filter. The algorithm is implemented on real-world hardware where experiments are carried out to reveal the advantages of the proposed method with respect to conventional ones. The proposed approach is also validated on an unmanned aerial vehicle during a real flight. Results show that the proposed one is faster than any other Kalman-based ones and even faster than some complementary ones while the attitude estimation accuracy is maintained.

scholarly journals Robust Sensor-Orientation-Independent Feature Selection for Animal Activity Recognition on Collar Tags

2018 ◽  
Vol 2 (1) ◽  
pp. 1-27 ◽  
Author(s):  
Jacob W. Kamminga ◽  
Duc V. Le ◽  
Jan Pieter Meijers ◽  
Helena Bisby ◽  
Nirvana Meratnia ◽  
...  
Keyword(s):  
Feature Selection ◽  
Activity Recognition ◽  
Sensor Orientation ◽  
Animal Activity ◽  
Selection For

scholarly journals UAV-LiCAM SYSTEM DEVELOPMENT: CALIBRATION AND GEO-REFERENCING

2018 ◽  
Vol XLII-1 ◽  
pp. 107-114 ◽  
Author(s):  
C. Cortes ◽  
M. Shahbazi ◽  
P. Ménard
Keyword(s):  
Particle Filtering ◽  
System Development ◽  
Low Cost ◽  
Base Station ◽  
Dual Frequency ◽  
Body Frame ◽  
Integrated Sensor ◽  
Sensor Orientation ◽  
Wide Range ◽  
Gnss Measurements

<p><strong>Abstract.</strong> In the last decade, applications of unmanned aerial vehicles (UAVs), as remote-sensing platforms, have extensively been investigated for fine-scale mapping, modeling and monitoring of the environment. In few recent years, integration of 3D laser scanners and cameras onboard UAVs has also received considerable attention as these two sensors provide complementary spatial/spectral information of the environment. Since lidar performs range and bearing measurements in its body-frame, precise GNSS/INS data are required to directly geo-reference the lidar measurements in an object-fixed coordinate system. However, such data comes at the price of tactical-grade inertial navigation sensors enabled with dual-frequency RTK-GNSS receivers, which also necessitates having access to a base station and proper post-processing software. Therefore, such UAV systems equipped with lidar and camera (UAV-LiCam Systems) are too expensive to be accessible to a wide range of users. Hence, new solutions must be developed to eliminate the need for costly navigation sensors. In this paper, a two-fold solution is proposed based on an in-house developed, low-cost system: 1) a multi-sensor self-calibration approach for calibrating the Li-Cam system based on planar and cylindrical multi-directional features; 2) an integrated sensor orientation method for georeferencing based on unscented particle filtering which compensates for time-variant IMU errors and eliminates the need for GNSS measurements.</p>

scholarly journals PERFORMANCE ASSESSMENT OF INTEGRATED SENSOR ORIENTATION WITH A LOW-COST GNSS RECEIVER

2017 ◽  
Vol IV-2/W3 ◽  
pp. 75-80 ◽  
Author(s):  
M. Rehak ◽  
J. Skaloud
Keyword(s):  
Position Control ◽  
Low Cost ◽  
Satellite System ◽  
Bundle Adjustment ◽  
Single Frequency ◽  
Reference Trajectory ◽  
Integrated Sensor ◽  
Homogeneous Surface ◽  
Gnss Receiver ◽  
Sensor Orientation

Mapping with Micro Aerial Vehicles (MAVs whose weight does not exceed 5&amp;thinsp;kg) is gaining importance in applications such as corridor mapping, road and pipeline inspections, or mapping of large areas with homogeneous surface structure, e.g. forest or agricultural fields. In these challenging scenarios, integrated sensor orientation (ISO) improves effectiveness and accuracy. Furthermore, in block geometry configurations, this mode of operation allows mapping without ground control points (GCPs). Accurate camera positions are traditionally determined by carrier-phase GNSS (Global Navigation Satellite System) positioning. However, such mode of positioning has strong requirements on receiver’s and antenna’s performance. In this article, we present a mapping project in which we employ a single-frequency, low-cost (<&amp;thinsp;$100) GNSS receiver on a MAV. The performance of the low-cost receiver is assessed by comparing its trajectory with a reference trajectory obtained by a survey-grade, multi-frequency GNSS receiver. In addition, the camera positions derived from these two trajectories are used as observations in bundle adjustment (BA) projects and mapping accuracy is evaluated at check points (ChP). Several BA scenarios are considered with absolute and relative aerial position control. Additionally, the presented experiments show the possibility of BA to determine a camera-antenna spatial offset, so-called lever-arm.

scholarly journals GNSS-Assisted Integrated Sensor Orientation with Sensor Pre-Calibration for Accurate Corridor Mapping

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2783 ◽  
Author(s):  
Yilin Zhou ◽  
Ewelina Rupnik ◽  
Paul-Henri Faure ◽  
Marc Pierrot-Deseilligny
Keyword(s):  
Satellite System ◽  
Sensor Calibration ◽  
Image Block ◽  
Integrated Sensor ◽  
Physical Constraints ◽  
Pose Determination ◽  
Sensor Orientation ◽  
Global Navigation Satellite ◽  
Oblique Images ◽  
The Impact

With the development of unmanned aerial vehicles (UAVs) and global navigation satellite system (GNSS), the accurate camera positions at exposure can be known and the GNSS-assisted bundle block adjustment (BBA) approach is possible for integrated sensor orientation (ISO). This study employed ISO approach for camera pose determination with the objective of investigating the impact of a good sensor pre-calibration on a poor acquisition geometry. Within the presented works, several flights were conducted on a dike by a small UAV embedded with a metric camera and a GNSS receiver. The multi-lever-arm estimation within the BBA procedure makes it possible to merge image blocks of different configurations such as nadir and oblique images without physical constraints on camera and GNSS antenna positions. The merged image block achieves a better accuracy and the sensor self-calibrated well. The issued sensor calibration is then applied to a less preferable acquisition configuration and the accuracy is significantly improved. For a corridor acquisition scene of about 600 m , a centimetric accuracy is reached with one GCP. With the provided sensor pre-calibration, an accuracy of 3.9 c m is achieved without any GCP.

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