scholarly journals COMPARISON BETWEEN RGB AND RGB-D CAMERAS FOR SUPPORTING LOW-COST GNSS URBAN NAVIGATION

2018 ◽  
Vol XLII-2 ◽  
pp. 991-998 ◽  
Author(s):  
L. Rossi ◽  
C. I. De Gaetani ◽  
D. Pagliari ◽  
E. Realini ◽  
M. Reguzzoni ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Urban Areas ◽  
Ad Hoc ◽  
Focal Length ◽  
Low Cost ◽  
Experimental Tests ◽  
Microsoft Kinect ◽  
Visual Data ◽  
Data Accessibility

A pure GNSS navigation is often unreliable in urban areas because of the presence of obstructions, thus preventing a correct reception of the satellite signal. The bridging between GNSS outages, as well as the vehicle attitude reconstruction, can be recovered by using complementary information, such as visual data acquired by RGB-D or RGB cameras. In this work, the possibility of integrating low-cost GNSS and visual data by means of an extended Kalman filter has been investigated. The focus is on the comparison between the use of RGB-D or RGB cameras. In particular, a Microsoft Kinect device (second generation) and a mirrorless Canon EOS M RGB camera have been compared. The former is an interesting RGB-D camera because of its low-cost, easiness of use and raw data accessibility. The latter has been selected for the high-quality of the acquired images and for the possibility of mounting fixed focal length lenses with a lower weight and cost with respect to a reflex camera. The designed extended Kalman filter takes as input the GNSS-only trajectory and the relative orientation between subsequent pairs of images. Depending on the visual data acquisition system, the filter is different because RGB-D cameras acquire both RGB and depth data, allowing to solve the scale problem, which is instead typical of image-only solutions. The two systems and filtering approaches were assessed by ad-hoc experimental tests, showing that the use of a Kinect device for supporting a u-blox low-cost receiver led to a trajectory with a decimeter accuracy, that is 15 % better than the one obtained when using the Canon EOS M camera.

scholarly journals A DCM Based Attitude Estimation Algorithm for Low-Cost MEMS IMUs

2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
Heikki Hyyti ◽  
Arto Visala
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Low Cost ◽  
Direction Cosine ◽  
Estimation Algorithm ◽  
Calibration Method ◽  
Attitude Estimation ◽  
Mems Sensors ◽  
Acceleration Sensors ◽  
Adaptive Extended Kalman Filter

An attitude estimation algorithm is developed using an adaptive extended Kalman filter for low-cost microelectromechanical-system (MEMS) triaxial accelerometers and gyroscopes, that is, inertial measurement units (IMUs). Although these MEMS sensors are relatively cheap, they give more inaccurate measurements than conventional high-quality gyroscopes and accelerometers. To be able to use these low-cost MEMS sensors with precision in all situations, a novel attitude estimation algorithm is proposed for fusing triaxial gyroscope and accelerometer measurements. An extended Kalman filter is implemented to estimate attitude in direction cosine matrix (DCM) formation and to calibrate gyroscope biases online. We use a variable measurement covariance for acceleration measurements to ensure robustness against temporary nongravitational accelerations, which usually induce errors when estimating attitude with ordinary algorithms. The proposed algorithm enables accurate gyroscope online calibration by using only a triaxial gyroscope and accelerometer. It outperforms comparable state-of-the-art algorithms in those cases when there are either biases in the gyroscope measurements or large temporary nongravitational accelerations present. A low-cost, temperature-based calibration method is also discussed for initially calibrating gyroscope and acceleration sensors. An open source implementation of the algorithm is also available.

A Multi-User Ad-Hoc Resource Manager for Public Urban Areas

2012 ◽  
pp. 306-319
Author(s):  
Gonzalo Huerta-Canepa ◽  
Dongman Lee
Keyword(s):  
Mobile Devices ◽  
Urban Areas ◽  
Ad Hoc ◽  
Current System ◽  
Low Cost ◽  
Smart Spaces ◽  
Resource Manager ◽  
Technological Infrastructure ◽  
Public Resources ◽  
Social Gain

Smart spaces are defined as an environment capable of communicating with users in order to support them in achieving a goal. Previously, smart spaces were restricted to closed private areas in a well defined environment. However, factors such as the omnipresence of mobile devices, the advancement in wireless communication, and the low cost of technological infrastructure allows the creation of smart spaces everywhere. One trend that is acquiring relevance these days is to use surrounding public resources to perform tasks on behalf of mobile devices, which are resource constrained. To achieve this, systems should be able to control the access to public resources, minimize possible interference among users, and maintain the purpose of public resources untouched. This work presents a multi-user ad-hoc resource manager for smart urban areas based on previous considerations. The current system helps to avoid conflicts between users by means of a distributed scheme based on social gain for the community. The management is performed without the need of a central infrastructure. Results show that it is possible to discover and manage public resources from mobile devices while handling conflicts in a distributed manner.

A Multi-User Ad-Hoc Resource Manager for Public Urban Areas

2012 ◽  
pp. 53-71 ◽  
Author(s):  
Gonzalo Huerta-Canepa ◽  
Dongman Lee
Keyword(s):  
Mobile Devices ◽  
Urban Areas ◽  
Ad Hoc ◽  
Current System ◽  
Low Cost ◽  
Smart Spaces ◽  
Resource Manager ◽  
Technological Infrastructure ◽  
Public Resources ◽  
Social Gain

Smart spaces are defined as an environment capable of communicating with users in order to support them in achieving a goal. Previously, smart spaces were restricted to closed private areas in a well defined environment. However, factors such as the omnipresence of mobile devices, the advancement in wireless communication, and the low cost of technological infrastructure allows the creation of smart spaces everywhere. One trend that is acquiring relevance these days is to use surrounding public resources to perform tasks on behalf of mobile devices, which are resource constrained. To achieve this, systems should be able to control the access to public resources, minimize possible interference among users, and maintain the purpose of public resources untouched. This work presents a multi-user ad-hoc resource manager for smart urban areas based on previous considerations. The current system helps to avoid conflicts between users by means of a distributed scheme based on social gain for the community. The management is performed without the need of a central infrastructure. Results show that it is possible to discover and manage public resources from mobile devices while handling conflicts in a distributed manner.

scholarly journals Performance Enhancement of Pedestrian Navigation Systems Based on Low-Cost Foot-Mounted MEMS-IMU/Ultrasonic Sensor

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 364 ◽  
Author(s):  
Ming Xia ◽  
Chundi Xiu ◽  
Dongkai Yang ◽  
Li Wang
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Navigation System ◽  
Low Cost ◽  
Ultrasonic Sensor ◽  
Measurement Unit ◽  
Positioning Error ◽  
Process Noise ◽  
Pedestrian Navigation ◽  
Mems Imu

The pedestrian navigation system (PNS) based on inertial navigation system-extended Kalman filter-zero velocity update (INS-EKF-ZUPT or IEZ) is widely used in complex environments without external infrastructure owing to its characteristics of autonomy and continuity. IEZ, however, suffers from performance degradation caused by the dynamic change of process noise statistics and heading estimation errors. The main goal of this study is to effectively improve the accuracy and robustness of pedestrian localization based on the integration of the low-cost foot-mounted microelectromechanical system inertial measurement unit (MEMS-IMU) and ultrasonic sensor. The proposed solution has two main components: (1) the fuzzy inference system (FIS) is exploited to generate the adaptive factor for extended Kalman filter (EKF) after addressing the mismatch between statistical sample covariance of innovation and the theoretical one, and the fuzzy adaptive EKF (FAEKF) based on the MEMS-IMU/ultrasonic sensor for pedestrians was proposed. Accordingly, the adaptive factor is applied to correct process noise covariance that accurately reflects previous state estimations. (2) A straight motion heading update (SMHU) algorithm is developed to detect whether a straight walk happens and to revise errors in heading if the ultrasonic sensor detects the distance between the foot and reflection point of the wall. The experimental results show that horizontal positioning error is less than 2% of the total travelled distance (TTD) in different environments, which is the same order of positioning error compared with other works using high-end MEMS-IMU. It is concluded that the proposed approach can achieve high performance for PNS in terms of accuracy and robustness.

scholarly journals Experimentally Validated Extended Kalman Filter for UAV State Estimation Using Low-Cost Sensors

2018 ◽  
Vol 51 (15) ◽  
pp. 43-48 ◽  
Author(s):  
S.P.H. Driessen ◽  
N.H.J. Janssen ◽  
L. Wang ◽  
J.L. Palmer ◽  
H. Nijmeijer
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Extended Kalman Filter ◽  
Low Cost

Comparison of the effects of nature sounds and reflexology on hemodynamic indices among traumatic comatose patients: A randomized controlled clinical trial

2019 ◽  
Vol 16 (3) ◽  
Author(s):  
Elahe Bahonar ◽  
Tahereh Najafi Ghezeljeh ◽  
Hamid Haghani
Keyword(s):  
Clinical Trial ◽  
Urban Areas ◽  
Ad Hoc ◽  
Low Cost ◽  
Sequential Sampling ◽  
Repeated Measure ◽  
Teaching Hospitals ◽  
Controlled Clinical Trial ◽  
Chi Square ◽  
And Control

Abstract Background Traumatic comatose patients may experience disturbances in hemodynamic indices due to the nature of their disorder. This study aimed to compare the effects of nature sounds and reflexology on hemodynamic indices in traumatic comatose patients. Methods This randomized clinical trial using a factorial design was conducted on 120 traumatic comatose patients in two teaching hospitals in two urban areas of Iran. The patients were selected using a sequential sampling method and assigned into randomized quadruple blocks as control, nature sounds, reflexology and nature sounds-reflexology (combined) groups. The interventions were performed twice daily in two consecutive days lasting 30 min each time. The hemodynamic indices were measured before, and immediately, 30 min, and 2 h after the intervention using calibrated monitors. Descriptive and inferential statistics, including one-way ANOVA, Scheffe ad hoc, repeated measure ANOVA, Bonferroni ad hoc Chi-square test and Fisher’s exact tests were used for data analysis via the SPSS software V.16. Results Significant differences were reported in terms of the mean arterial pressure between the control and reflexology groups (p=0.002), and the combined group (p=0.008) immediately after the interventions. The combined group showed statistically differences in systolic blood pressure compared to the nature sounds (p=0.007) and control (p=0.015) groups 30 min after the interventions. The nature sounds group showed differences in the pulse rate from the reflexology (p=0.048) and control (p=0.015) groups 30 min after the interventions in the second day. Conclusions While the immediate effects of the interventions on induction of the feeling of relaxation and tranquility, and reduction of hemodynamic indices were reported, they diminished over time. Nature sounds and reflexology as low-cost and relaxing tranquilizing methods can be used for the reduction of tension and improvement of hemodynamic indices among traumatic comatose patients.

Design and Implementation of Sensing and Estimation Software in AggieNav, a Small UAV Navigation Platform

2009 ◽  
Author(s):  
Calvin Coopmans ◽  
Haiyang Chao ◽  
YangQuan Chen
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Low Cost ◽  
High Accuracy ◽  
Level System ◽  
Design And Implementation ◽  
Small Uav ◽  
High Level ◽  
Navigational Systems ◽  
Uav Navigation

Small UAV performance is limited by the sensors and software filters used in the navigational systems. Several solutions of various complexity and cost exist, however no ready-made solutions exist for a high-accuracy, low-cost UAV system. Presented is the design (low-level system as well as high-level extended Kalman filter) for a specifically designed small-UAV navigation platform, AggieNav.

Extended Kalman Filter Based In-Cylinder Temperature Estimation for Diesel Engines With Thermocouple Lag Compensation

2014 ◽  
Vol 136 (5) ◽  
Author(s):  
Song Chen ◽  
Fengjun Yan
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Diesel Engines ◽  
Measurement Errors ◽  
Low Cost ◽  
Estimation Method ◽  
Measured Temperature ◽  
Temperature Estimation ◽  
Engine Model ◽  
Auto Ignition

The in-cylinder temperature information is critical for auto-ignition combustion control in diesel engines, but difficult to be directly accessed at low cost in production engines. Through investigating the thermodynamics of Tivc, cycle-by-cycle models are proposed in this paper for the estimation of in-cylinder temperature at the crank angle of intake valve closing (IVC), referred to as Tivc. An extended Kalman filter (EKF) based method was devised by utilizing the measurable temperature information from the intake and exhaust manifolds. Due to the fact that measured temperature signals by typical thermocouples have slow responses which can be modeled as first-order lags with varying time-constants, temperature signals need to be reconstructed in transient conditions. In the proposed EKF estimation method, this issue can be effectively addressed by analyzing the measurement errors and properly selecting the noises covariance matrices. The proposed estimation method was validated through a high-fidelity GT-power engine model.

scholarly journals On-Body Characterization of Planar Differential Antennas for Multiple, Wide, and Narrow Bands

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Luigi Vallozzi ◽  
Domenico Pepe ◽  
Thijs Castel ◽  
Hendrik Rogier ◽  
Domenico Zito
Keyword(s):  
Human Body ◽  
Ad Hoc ◽  
Low Cost ◽  
Experimental Tests ◽  
Body Measurements ◽  
Antenna Performance ◽  
Sensing Applications ◽  
The Impact ◽  
Narrow Bands

This paper reports the results of the on-body experimental tests of a set of four planar differential antennas, originated by design variations of radiating elements with the same shape and characterized by the potential for covering wide and narrow bands. All the antenna designs have been implemented on low-cost FR4 substrate and characterized experimentally through on-body measurements. The results show the impact of the proximity to the human body on antenna performance and the opportunities in terms of potential coverage of wide and narrow bands for future ad hoc designs and implementations through wearable substrates targeting on-body and off-body communication and sensing applications.

scholarly journals USE OF ASSISTED PHOTOGRAMMETRY FOR INDOOR AND OUTDOOR NAVIGATION PURPOSES

2015 ◽  
Vol XL-4/W5 ◽  
pp. 113-118 ◽  
Author(s):  
D. Pagliari ◽  
N. E. Cazzaniga ◽  
L. Pinto
Keyword(s):  
Urban Areas ◽  
Low Cost ◽  
Point Clouds ◽  
Satellite System ◽  
Indoor Navigation ◽  
Microsoft Kinect ◽  
Textured Surfaces ◽  
Navigation Problem ◽  
Additional Information ◽  
Outdoor Navigation

Nowadays, devices and applications that require navigation solutions are continuously growing. For instance, consider the increasing demand of mapping information or the development of applications based on users’ location. In some case it could be sufficient an approximate solution (e.g. at room level), but in the large amount of cases a better solution is required. <br><br> The navigation problem has been solved from a long time using Global Navigation Satellite System (GNSS). However, it can be unless in obstructed areas, such as in urban areas or inside buildings. An interesting low cost solution is photogrammetry, assisted using additional information to scale the photogrammetric problem and recovering a solution also in critical situation for image-based methods (e.g. poor textured surfaces). In this paper, the use of assisted photogrammetry has been tested for both outdoor and indoor scenarios. Outdoor navigation problem has been faced developing a positioning system with Ground Control Points extracted from urban maps as constrain and tie points automatically extracted from the images acquired during the survey. The proposed approach has been tested under different scenarios, recovering the followed trajectory with an accuracy of 0.20 m. <br><br> For indoor navigation a solution has been thought to integrate the data delivered by Microsoft Kinect, by identifying interesting features on the RGB images and re-projecting them on the point clouds generated from the delivered depth maps. Then, these points have been used to estimate the rotation matrix between subsequent point clouds and, consequently, to recover the trajectory with few centimeters of error.

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