scholarly journals THE GENERATION OF BUILDING FLOOR PLANS USING PORTABLE AND UNMANNED AERIAL VEHICLE MAPPING SYSTEMS

2016 ◽  
Vol XLI-B4 ◽  
pp. 331-337
Author(s):  
G. J. Tsai ◽  
Y. L. Chen ◽  
K. W. Chiang ◽  
Y. C. Lai
Keyword(s):  
Coordinate System ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Survey Method ◽  
Mapping Technique ◽  
Positioning Systems ◽  
Mapping System ◽  
Floor Plans ◽  
Control Survey ◽  
Mapping Systems

Indoor navigation or positioning systems have been widely developed for Location-Based Services (LBS) applications and they come along with a keen demand of indoor floor plans for displaying results even improving the positioning performance. Generally, the floor plans produced by robot mapping focus on perceiving the environment to avoid obstacles and using the feature landmarks to update the robot position in the relative coordinate frame. These maps are not accurate enough to incorporate to the indoor positioning system. This study aims at developing Indoor Mobile Mapping System (Indoor MMS) and concentrates on generating the highly accurate floor plans based on the robot mapping technique using the portable, robot and Unmanned Aerial Vehicles (UAV) platform. The proposed portable mapping system prototype can be used in the chest package and the handheld approach. In order to evaluate and correct the generated floor plans from robot mapping techniques, this study builds the testing and calibration field using the outdoor control survey method implemented in the indoor environments. Based on control points and check points from control survey, this study presents the map rectification method that uses the affine transformation to solve the scale and deformation problems and also transfer the local coordinate system into world standard coordinate system. The preliminary results illustrate that the final version of the building floor plan reach 1 meter absolute positioning accuracy using the proposed mapping systems that combines with the novel map rectification approach proposed. These maps are well geo-referenced with world coordinate system thus it can be applied for future seamless navigation applications including indoor and outdoor scenarios.

scholarly journals THE GENERATION OF BUILDING FLOOR PLANS USING PORTABLE AND UNMANNED AERIAL VEHICLE MAPPING SYSTEMS

2016 ◽  
Vol XLI-B4 ◽  
pp. 331-337
Author(s):  
G. J. Tsai ◽  
Y. L. Chen ◽  
K. W. Chiang ◽  
Y. C. Lai
Keyword(s):  
Coordinate System ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Survey Method ◽  
Mapping Technique ◽  
Positioning Systems ◽  
Mapping System ◽  
Floor Plans ◽  
Control Survey ◽  
Mapping Systems

Indoor navigation or positioning systems have been widely developed for Location-Based Services (LBS) applications and they come along with a keen demand of indoor floor plans for displaying results even improving the positioning performance. Generally, the floor plans produced by robot mapping focus on perceiving the environment to avoid obstacles and using the feature landmarks to update the robot position in the relative coordinate frame. These maps are not accurate enough to incorporate to the indoor positioning system. This study aims at developing Indoor Mobile Mapping System (Indoor MMS) and concentrates on generating the highly accurate floor plans based on the robot mapping technique using the portable, robot and Unmanned Aerial Vehicles (UAV) platform. The proposed portable mapping system prototype can be used in the chest package and the handheld approach. In order to evaluate and correct the generated floor plans from robot mapping techniques, this study builds the testing and calibration field using the outdoor control survey method implemented in the indoor environments. Based on control points and check points from control survey, this study presents the map rectification method that uses the affine transformation to solve the scale and deformation problems and also transfer the local coordinate system into world standard coordinate system. The preliminary results illustrate that the final version of the building floor plan reach 1 meter absolute positioning accuracy using the proposed mapping systems that combines with the novel map rectification approach proposed. These maps are well geo-referenced with world coordinate system thus it can be applied for future seamless navigation applications including indoor and outdoor scenarios.

scholarly journals Indoor Positioning System: A New Approach Based on LSTM and Two Stage Activity Classification

Electronics ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 375 ◽  
Author(s):  
Ghulam Hussain ◽  
Muhammad Jabbar ◽  
Jun-Dong Cho ◽  
Sangmin Bae
Keyword(s):  
Short Term Memory ◽  
Inertial Sensors ◽  
Recognition Task ◽  
Indoor Positioning ◽  
Physical Activities ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Average Error ◽  
Positioning Systems ◽  
Localization Performance

The number of studies on the development of indoor positioning systems has increased recently due to the growing demands of the various location-based services. Inertial sensors available in commercial smartphones play an important role in indoor localization and navigation owing to their highly accurate localization performance. In this study, the inertial sensors of a smartphone, which generate distinct patterns for physical activities and action units (AUs), are employed to localize a target in an indoor environment. These AUs, (such as a left turn, right turn, normal step, short step, or long step), help to accurately estimate the indoor location of a target. By taking advantage of sophisticated deep learning algorithms, we propose a novel approach for indoor navigation based on long short-term memory (LSTM). The LSTM accurately recognizes physical activities and related AUs by automatically extracting the efficient features from the distinct patterns of the input data. Experiment results show that LSTM provides a significant improvement in the indoor positioning performance through the recognition task. The proposed system achieves a better localization performance than the trivial fingerprinting method, with an average error of 0.782 m in an indoor area of 128.6 m2. Additionally, the proposed system exhibited robust performance by excluding the abnormal activity from the pedestrian activities.

scholarly journals RETHINKING INDOOR LOCALIZATION SOLUTIONS TOWARDS THE FUTURE OF MOBILE LOCATION-BASED SERVICES

2017 ◽  
Vol IV-4/W4 ◽  
pp. 235-247 ◽  
Author(s):  
C. Guney
Keyword(s):  
Indoor Localization ◽  
Smart Cities ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Outdoor Environment ◽  
Indoor Environments ◽  
Navigation Systems ◽  
Positioning Systems ◽  
Indoor Location ◽  
High Level

Satellite navigation systems with GNSS-enabled devices, such as smartphones, car navigation systems, have changed the way users travel in outdoor environment. GNSS is generally not well suited for indoor location and navigation because of two reasons: First, GNSS does not provide a high level of accuracy although indoor applications need higher accuracies. Secondly, poor coverage of satellite signals for indoor environments decreases its accuracy. So rather than using GNSS satellites within closed environments, existing indoor navigation solutions rely heavily on installed sensor networks. There is a high demand for accurate positioning in wireless networks in GNSS-denied environments. However, current wireless indoor positioning systems cannot satisfy the challenging needs of indoor location-aware applications. Nevertheless, access to a user’s location indoors is increasingly important in the development of context-aware applications that increases business efficiency. In this study, how can the current wireless location sensing systems be tailored and integrated for specific applications, like smart cities/grids/buildings/cars and IoT applications, in GNSS-deprived areas.

scholarly journals STATISTICAL SENSOR FUSION OF A 9-DOF MEMS IMU FOR INDOOR NAVIGATION

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 333-338 ◽  
Author(s):  
J. C. K. Chow
Keyword(s):  
Sensor Fusion ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Ultra Wideband ◽  
Position Information ◽  
Positioning Systems ◽  
Pose Tracking ◽  
The Dead ◽  
Mems Imu

Sensor fusion of a MEMS IMU with a magnetometer is a popular system design, because such 9-DoF (degrees of freedom) systems are capable of achieving drift-free 3D orientation tracking. However, these systems are often vulnerable to ambient magnetic distortions and lack useful position information; in the absence of external position aiding (e.g. satellite/ultra-wideband positioning systems) the dead-reckoned position accuracy from a 9-DoF MEMS IMU deteriorates rapidly due to unmodelled errors. Positioning information is valuable in many satellite-denied geomatics applications (e.g. indoor navigation, location-based services, etc.). This paper proposes an improved 9-DoF IMU indoor pose tracking method using batch optimization. By adopting a robust in-situ user self-calibration approach to model the systematic errors of the accelerometer, gyroscope, and magnetometer simultaneously in a tightly-coupled post-processed least-squares framework, the accuracy of the estimated trajectory from a 9-DoF MEMS IMU can be improved. Through a combination of relative magnetic measurement updates and a robust weight function, the method is able to tolerate a high level of magnetic distortions. The proposed auto-calibration method was tested in-use under various heterogeneous magnetic field conditions to mimic a person walking with the sensor in their pocket, a person checking their phone, and a person walking with a smartwatch. In these experiments, the presented algorithm improved the in-situ dead-reckoning orientation accuracy by 79.8–89.5 % and the dead-reckoned positioning accuracy by 72.9–92.8 %, thus reducing the relative positioning error from metre-level to decimetre-level after ten seconds of integration, without making assumptions about the user’s dynamics.

scholarly journals S-PDR: SBAUPT-Based Pedestrian Dead Reckoning Algorithm for Free-Moving Handheld Devices

Geomatics ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 148-176
Author(s):  
Maan Khedr ◽  
Naser El-Sheimy
Keyword(s):  
Smart Cities ◽  
Dead Reckoning ◽  
Human Motion ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Navigation Systems ◽  
Short Term ◽  
Navigation Solution ◽  
Correction Technique ◽  
Pedestrian Dead Reckoning

Mobile location-based services (MLBS) are attracting attention for their potential public and personal use for a variety of applications such as location-based advertisement, smart shopping, smart cities, health applications, emergency response, and even gaming. Many of these applications rely on Inertial Navigation Systems (INS) due to the degraded GNSS services indoors. INS-based MLBS using smartphones is hindered by the quality of the MEMS sensors provided in smartphones which suffer from high noise and errors resulting in high drift in the navigation solution rapidly. Pedestrian dead reckoning (PDR) is an INS-based navigation technique that exploits human motion to reduce navigation solution errors, but the errors cannot be eliminated without aid from other techniques. The purpose of this study is to enhance and extend the short-term reliability of PDR systems for smartphones as a standalone system through an enhanced step detection algorithm, a periodic attitude correction technique, and a novel PCA-based motion direction estimation technique. Testing shows that the developed system (S-PDR) provides a reliable short-term navigation solution with a final positioning error that is up to 6 m after 3 min runtime. These results were compared to a PDR solution using an Xsens IMU which is known to be a high grade MEMS IMU and was found to be worse than S-PDR. The findings show that S-PDR can be used to aid GNSS in challenging environments and can be a viable option for short-term indoor navigation until aiding is provided by alternative means. Furthermore, the extended reliable solution of S-PDR can help reduce the operational complexity of aiding navigation systems such as RF-based indoor navigation and magnetic map matching as it reduces the frequency by which these aiding techniques are required and applied.

scholarly journals Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor Positioning

2021 ◽  
Vol 11 (15) ◽  
pp. 6805
Author(s):  
Khaoula Mannay ◽  
Jesús Ureña ◽  
Álvaro Hernández ◽  
José M. Villadangos ◽  
Mohsen Machhout ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Experimental Tests ◽  
Indoor Positioning ◽  
Location Based Services ◽  
Smart Devices ◽  
Final Position ◽  
Positioning Systems ◽  
Local Positioning System ◽  
Tightly Coupled ◽  
Position Estimate

Indoor positioning systems have become a feasible solution for the current development of multiple location-based services and applications. They often consist of deploying a certain set of beacons in the environment to create a coverage volume, wherein some receivers, such as robots, drones or smart devices, can move while estimating their own position. Their final accuracy and performance mainly depend on several factors: the workspace size and its nature, the technologies involved (Wi-Fi, ultrasound, light, RF), etc. This work evaluates a 3D ultrasonic local positioning system (3D-ULPS) based on three independent ULPSs installed at specific positions to cover almost all the workspace and position mobile ultrasonic receivers in the environment. Because the proposal deals with numerous ultrasonic emitters, it is possible to determine different time differences of arrival (TDOA) between them and the receiver. In that context, the selection of a suitable fusion method to merge all this information into a final position estimate is a key aspect of the proposal. A linear Kalman filter (LKF) and an adaptive Kalman filter (AKF) are proposed in that regard for a loosely coupled approach, where the positions obtained from each ULPS are merged together. On the other hand, as a tightly coupled method, an extended Kalman filter (EKF) is also applied to merge the raw measurements from all the ULPSs into a final position estimate. Simulations and experimental tests were carried out and validated both approaches, thus providing average errors in the centimetre range for the EKF version, in contrast to errors up to the meter range from the independent (not merged) ULPSs.

Constructing Floor Plan through Smoke Using Ultra Wideband Radar

2021 ◽  
Vol 5 (4) ◽  
pp. 1-29
Author(s):  
Weiyan Chen ◽  
Fusang Zhang ◽  
Tao Gu ◽  
Kexing Zhou ◽  
Zixuan Huo ◽  
...  
Keyword(s):  
Spatial Information ◽  
Low Cost ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Ultra Wideband ◽  
Indoor Environments ◽  
Floor Plan ◽  
Construction Methods ◽  
Median Error ◽  
Indoor Scenarios

Floor plan construction has been one of the key techniques in many important applications such as indoor navigation, location-based services, and emergency rescue. Existing floor plan construction methods require expensive dedicated hardware (e.g., Lidar or depth camera), and may not work in low-visibility environments (e.g., smoke, fog or dust). In this paper, we develop a low-cost Ultra Wideband (UWB)-based system (named UWBMap) that is mounted on a mobile robot platform to construct floor plan through smoke. UWBMap leverages on low-cost and off-the-shelf UWB radar, and it is able to construct an indoor map with an accuracy comparable to Lidar (i.e., the state-of-the-art). The underpinning technique is to take advantage of the mobility of radar to form virtual antennas and gather spatial information of a target. UWBMap also eliminates both robot motion noise and environmental noise to enhance weak reflection from small objects for the robust construction process. In addition, we overcome the limited view of single radar by combining multi-view from multiple radars. Extensive experiments in different indoor environments show that UWBMap achieves a map construction with a median error of 11 cm and a 90-percentile error of 26 cm, and it operates effectively in indoor scenarios with glass wall and dense smoke.

scholarly journals Visual-Inertial Odometer-Based Global High Precision Indoor Human Navigation in a University Library

2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Shinpei Ito ◽  
Akinori Takahashi ◽  
Ruochen Si ◽  
Masatoshi Arikawa
Keyword(s):  
Coordinate System ◽  
High Precision ◽  
Real World ◽  
Indoor Navigation ◽  
Experimental Result ◽  
Coordinate Space ◽  
Central Position ◽  
Global Coordinate System ◽  
Prototype System ◽  
3D Environments

<p><strong>Abstract.</strong> AR (Augmented Reality) could be realized as a basic and high-level function on latest smartphones with a reasonable price. AR enables users to experience consistent three-dimensional (3D) spaces co-existing with 3D real and virtual objects with sensing real 3D environments and reconstructing them in the virtual world through a camera. The accuracy of sensing real 3D environments using an AR function, that is, visual-inertial odometer, of a smartphone is extremely higher than one of a GPS receiver on it, and can be less than one centimeter. However, current common AR applications generally focus on “small” real 3D spaces, not large real 3D spaces. In other words, most of the current AR applications are not designed for uses based on a geographic coordinate system.</p><p>We proposed a global extension of the visual-inertial odometer with an image recognition function of geo-referenced image markers installed in real 3D spaces. Examples of geo-referenced image markers can be generated from analog guide boards existing in the real world. We tested this framework of a global extension of the visual-inertial odometer embedded in a smartphone on the first floor in the central library of Akita University. The geo-referenced image markers such as floor map boards and book categories sign boards were registered in a database of 3D geo-referenced real-world scene images. Our prototype system developed on a smartphone, that is, iPhone XS, Apple Inc., could first recognized a floor map board (Fig. 1), and could determine the 3D precise distance and direction of the smartphone from the central position of the floor map board in a local 3D coordinate space with the origin point as the central positon of the board. Then, the system could convert the relative precise position and the relative direction of the smartphone’s camera in a local coordinate space into a global precise location and orientation of it. A subject was walking the first floor in the building of the library with a world tracking function of the smartphone. The experimental result shows that the error of tracking a real 3D space of a global coordinate system was accumulated, but not bad. The accumulated error was only about 30 centimeters after the subject’s walking about 30 meters (Fig. 2). We are now planning to improve our prototype system in the accuracy of indoor navigation with calibrating the location and orientation of a smartphone based sequential recognitions of multiple referenced scene image markers which have already existed for a general user services of the library before developing this proposed new services. As the conclusion, the experiment’s result of testing our prototype system was impressive, we are now preparing a more practical high-precision LBS which enables a user to be navigated to the exact location of a book of a user’s interest in a bookshelf on a floor with AR and floor map interfaces.</p>

scholarly journals Penerapan Model Multivariat Analisis of Variance dalam Mengukur Persepsi Destinasi Wisata

2012 ◽  
Vol 3 (1) ◽  
pp. 461
Author(s):  
Robert Tang Herman
Keyword(s):  
Classification System ◽  
Business Performance ◽  
Secondary Data ◽  
Primary Data ◽  
Survey Method ◽  
Market Growth ◽  
Potential Market ◽  
Mapping System ◽  
Market Responsiveness ◽  
Market Needs

The purpose of this research is to provide conceptual and infrastructure tools for Dinas Pariwisata DKI Jakarta to improve their capabilities for evaluating business performance based on market responsiveness. Capturing market responsiveness is the initial research to make industry mapping. Research steps started with secondary research to build data classification system. The second is primary research by collecting the data from market research. Data sources for secondary data were collected from Dinas Pariwisata DKI, while the primary data were collected from survey method using quetionaires addressed to the whole market. Then, analyze the data colleted with multivariate analysis of variance to develop the mapping. The result of cluster analysis distinguishes the potential market based on their responses to the industry classification, make the classification system, find the gaps and how important are they, and the another issue related to the role of the mapping system. So, this mapping system will help Dinas Pariwisata DKI to improve capabilities and the business performance based on the market responsiveness and, which is the potential market for each specific classification, know what their needs, wants and demand from that classification. This research contribution can be used to give the recommendation to Dinas Pariwisata DKI to deliver what market needs and wants to all the tourism place based on this classification resulting, to develop the market growth estimation; and for the long term is to improve the economic and market growth.

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