scholarly journals Multi-Sensor Accurate Forklift Location and Tracking Simulation in Industrial Indoor Environments

Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1152 ◽  
Author(s):  
Valentín Barral ◽  
Pedro Suárez-Casal ◽  
Carlos J. Escudero ◽  
José A. García-Naya
Keyword(s):  
Inertial Sensor ◽  
Wireless Channel ◽  
Good Choice ◽  
Ultra Wideband ◽  
Positioning System ◽  
Indoor Environments ◽  
Location Algorithm ◽  
Industrial Environments ◽  
Indoor Scenarios ◽  
Industrial Problem

Location and tracking needs are becoming more prominent in industrial environments nowadays. Process optimization, traceability or safety are some of the topics where a positioning system can operate to improve and increase the productivity of a factory or warehouse. Among the different options, solutions based on ultra-wideband (UWB) have emerged during recent years as a good choice to obtain highly accurate estimations in indoor scenarios. However, the typical harsh wireless channel conditions found inside industrial environments, together with interferences caused by workers and machinery, constitute a challenge for this kind of system. This paper describes a real industrial problem (location and tracking of forklift trucks) that requires precise internal positioning and presents a study on the feasibility of meeting this challenge using UWB technology. To this end, a simulator of this technology was created based on UWB measurements from a set of real sensors. This simulator was used together with a location algorithm and a physical model of the forklift to obtain estimations of position in different scenarios with different obstacles. Together with the simulated UWB sensor, an additional inertial sensor and optical sensor were modeled in order to test its effect on supporting the location based on UWB. All the software created for this work is published under an open-source license and is publicly available.

UWB Positioning Systsem Design: Selection of Modulation and Multiple Access Schemes

2007 ◽  
Vol 61 (1) ◽  
pp. 45-62 ◽  
Author(s):  
Hui Yu ◽  
Enrique Aguado ◽  
Gary Brodin ◽  
John Cooper ◽  
David Walsh ◽  
...  
Keyword(s):  
Multiple Access ◽  
High Performance ◽  
Ultra Wideband ◽  
Good Time ◽  
Modulation Scheme ◽  
Positioning System ◽  
Indoor Environments ◽  
Signal Design ◽  
Positioning Systems ◽  
Design Selection

In densely-populated cities or indoor environments, limited visibility to satellites and severe multipath effects significantly affect the accuracy and reliability of satellite-based positioning systems. To meet the needs of “seamless navigation” in these challenging environments an advanced terrestrial positioning system is under development. This system is based upon Ultra-Wideband (UWB) technology, which is a promising candidate for this application due to good time domain resolution and immunity to multipath. This paper presents a detailed analysis of two key aspects of the UWB signal design that will allow it to be used as the basis of such a high performance positioning system: the modulation scheme and the multiple access technique. These two aspects are evaluated in terms of spectral efficiency and synchronisation performance over multipath channels. Thus this paper identifies optimal modulation and multiple access techniques for a long range, high performance terrestrial positioning system using UWB.

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 Integrated IMU with Faster R-CNN Aided Visual Measurements from IP Cameras for Indoor Positioning

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3134 ◽  
Author(s):  
Lin Zhang ◽  
Taoyun Zhou ◽  
Baowang Lian
Keyword(s):  
Indoor Positioning ◽  
Ultra Wideband ◽  
Measurement Unit ◽  
Indoor Environments ◽  
Inertial Measurement ◽  
Positioning Errors ◽  
Measurement Units ◽  
Stationary Obstacles ◽  
Indoor Scenarios ◽  
Visual Measurements

Considering the radio-based indoor positioning system pertaining to signal degradation due to the environmental factors, and rising popularity of IP (Internet Protocol) cameras in cities, a novel fusion of inertial measurement units (IMUs) with external IP cameras to determine the positions of moving users in indoor environments is presented. This approach uses a fine-tuned Faster R-CNN (Region Convolutional Neural Network) to detect users in images captured by cameras, and acquires visual measurements including ranges and angles of users with respect to the cameras based on the proposed monocular vision relatively measuring (MVRM) method. The results are determined by integrating the positions predicted by each user’s inertial measurement unit (IMU) and visual measurements using an EKF (Extended Kalman Filter). The results experimentally show that the ranging accuracy is affected by both the detected bounding box’s by Faster R-CNN height errors and diverse measuring distances, however, the heading accuracy is solely interfered with bounding box’s horizontal biases. The indoor obstacles including stationary obstacles and a pedestrian in our tests more significantly decrease the accuracy of ranging than that of heading, and the effect of a pedestrian on the heading errors is greater than stationary obstacles on that. We implemented a positioning test for a single user and an external camera in five indoor scenarios to evaluate the performance. The robust fused IMU/MVRM solution significantly decreases the positioning errors and shows better performance in dense multipath scenarios compared with the pure MVRM solution and ultra-wideband (UWB) solution.

Ultra-Wideband-Based Localization for Quadcopter Navigation

2016 ◽  
Vol 04 (01) ◽  
pp. 23-34 ◽  
Author(s):  
Kexin Guo ◽  
Zhirong Qiu ◽  
Cunxiao Miao ◽  
Abdul Hanif Zaini ◽  
Chun-Lin Chen ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Global Positioning System ◽  
Ultra Wideband ◽  
Line Of Sight ◽  
Positioning System ◽  
Localization Algorithm ◽  
Control Loop ◽  
Flight Tests ◽  
Localization System ◽  
Global Positioning

Micro unmanned aerial vehicles (UAVs) are promising to play more and more important roles in both civilian and military activities. Currently, the navigation of UAVs is critically dependent on the localization service provided by the Global Positioning System (GPS), which suffers from the multipath effect and blockage of line-of-sight, and fails to work in an indoor, forest or urban environment. In this paper, we establish a localization system for quadcopters based on ultra-wideband (UWB) range measurements. To achieve the localization, a UWB module is installed on the quadcopter to actively send ranging requests to some fixed UWB modules at known positions (anchors). Once a distance is obtained, it is calibrated first and then goes through outlier detection before being fed to a localization algorithm. The localization algorithm is initialized by trilateration and sustained by the extended Kalman filter (EKF). The position and velocity estimates produced by the algorithm will be further fed to the control loop to aid the navigation of the quadcopter. Various flight tests in different environments have been conducted to validate the performance of UWB ranging and localization algorithm.

scholarly journals Induced Magnetic Field-Based Indoor Positioning System for Underwater Environments

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2218
Author(s):  
Sizhen Bian ◽  
Peter Hevesi ◽  
Leif Christensen ◽  
Paul Lukowicz
Keyword(s):  
Magnetic Field ◽  
Low Cost ◽  
Autonomous Underwater Vehicles ◽  
Wide Band ◽  
Propagation Delay ◽  
Positioning System ◽  
Indoor Environments ◽  
Coverage Area ◽  
Underwater Positioning ◽  
Similar Accuracy

Autonomous underwater vehicles (AUV) are seen as an emerging technology for maritime exploration but are still restricted by the availability of short range, accurate positioning methods necessary, e.g., when docking remote assets. Typical techniques used for high-accuracy positioning in indoor use case scenarios, such as systems using ultra-wide band radio signals (UWB), cannot be applied for underwater positioning because of the quick absorption of the positioning medium caused by the water. Acoustic and optic solutions for underwater positioning also face known problems, such as the multi-path effects, high propagation delay (acoustics), and environmental dependency. This paper presents an oscillating magnetic field-based indoor and underwater positioning system. Unlike those radio wave-based positioning modalities, the magnetic approach generates a bubble-formed magnetic field that will not be deformed by the environmental variation because of the very similar permeability of water and air. The proposed system achieves an underwater positioning mean accuracy of 13.3 cm in 2D and 19.0 cm in 3D with the multi-lateration positioning method and concludes the potential of the magnetic field-based positioning technique for underwater applications. A similar accuracy was also achieved for various indoor environments that were used to test the influence of cluttered environment and of cross environment. The low cost and power consumption system is scalable for extensive coverage area and could plug-and-play without pre-calibration.

scholarly journals Practical Fingerprinting Localization for Indoor Positioning System by Using Beacons

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Santosh Subedi ◽  
Jae-Young Pyun
Keyword(s):  
Estimation Error ◽  
Indoor Positioning ◽  
Location Estimation ◽  
Reference Points ◽  
Ultra Wideband ◽  
Positioning System ◽  
Localization Method ◽  
Weighted Centroid Localization ◽  
Time Required ◽  
Indoor Positioning System

Recent developments in the fields of smartphones and wireless communication technologies such as beacons, Wi-Fi, and ultra-wideband have made it possible to realize indoor positioning system (IPS) with a few meters of accuracy. In this paper, an improvement over traditional fingerprinting localization is proposed by combining it with weighted centroid localization (WCL). The proposed localization method reduces the total number of fingerprint reference points over the localization space, thus minimizing both the time required for reading radio frequency signals and the number of reference points needed during the fingerprinting learning process, which eventually makes the process less time-consuming. The proposed positioning has two major steps of operation. In the first step, we have realized fingerprinting that utilizes lightly populated reference points (RPs) and WCL individually. Using the location estimated at the first step, WCL is run again for the final location estimation. The proposed localization technique reduces the number of required fingerprint RPs by more than 40% compared to normal fingerprinting localization method with a similar localization estimation error.

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