scholarly journals Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder

2019 ◽  
Vol 15 (7) ◽  
pp. 155014771986099 ◽  
Author(s):  
Yulu Fu ◽  
Ran Liu ◽  
Hua Zhang ◽  
Gaoli Liang ◽  
Shafiq ur Rehman ◽  
...  
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Spatial Clustering ◽  
Laser Ranging ◽  
Laser Range Finder ◽  
Two Dimensional ◽  
Range Finder ◽  
Laser Range ◽  
Frequency Identification ◽  
Velocity Matching

Due to the unique and contactless way of identification, radio-frequency identification is becoming an emerging technology for objects tracking. As radio-frequency identification does not provide any distance or bearing information, positioning using radio-frequency identification sensor itself is challenging. Two-dimensional laser range finders can provide the distance to the objects but require complicated recognition algorithms to acquire the identity of object. This article proposes an innovative method to track the locations of dynamic objects by combining radio-frequency identification and laser ranging information. We first segment the laser ranging data into clusters using density-based spatial clustering of applications with noise (DBSCAN). Velocity matching–based approach is used to track the location of object when the object is in the radio-frequency identification reading range. Since the radio-frequency identification reading range is smaller than a two-dimensional laser range finder, velocity matching–based approach fails to track location of the object when the radio-frequency identification reading is not available. In this case, our approach uses the clustering results from density-based spatial clustering of applications with noise to continuously track the moving object. Finally, we verified our approach on a Scitos robot in an indoor environment, and our results show that the proposed approach reaches a positioning accuracy of 0.43 m, which is an improvement of 67.6% and 84.1% as compared to laser-based and velocity matching–based approaches, respectively.

scholarly journals Localization of Moving Objects Based on RFID Tag Array and Laser Ranging Information

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 887 ◽  
Author(s):  
Shafiq Ur Rehman ◽  
Ran Liu ◽  
Hua Zhang ◽  
Gaoli Liang ◽  
Yulu Fu ◽  
...  
Keyword(s):  
Radial Velocity ◽  
Radio Frequency Identification ◽  
Moving Objects ◽  
Spatial Clustering ◽  
Service Robot ◽  
Laser Ranging ◽  
Localization Accuracy ◽  
Rfid Tag ◽  
Radio Signals ◽  
Frequency Identification

RFID (radio-frequency identification) technology is rapidly emerging for the localization of moving objects and humans. Due to the blockage of radio signals by the human body, the localization accuracy achieved with a single tag is not satisfactory. This paper proposes a method based on an RFID tag array and laser ranging information to address the localization of live moving objects such as humans or animals. We equipped a human with a tag array and calculated the phase-based radial velocity of every tag. The laser information was, first, clustered through the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm and then laser-based radial velocity was calculated. This velocity was matched with phase-based radial velocity to get best matching clusters. A particle filter was used to localize the moving human by fusing the matching results of both velocities. Experiments were conducted by using a SCITOS G5 service robot. The results verified the feasibility of our approach and proved that our approach significantly increases localization accuracy by up to 25% compared to a single tag approach.

Understanding RFID (Radio Frequency Identification)

2010 ◽  
pp. 54-64
Author(s):  
Susan A. Vowels
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Human Interaction ◽  
Automatic Identification ◽  
Two Dimensional ◽  
Product Usage ◽  
Bar Code ◽  
Label Information ◽  
Frequency Identification ◽  
Accepted Part

RFID, also known as radio frequency identification, is a form of Auto ID (automatic identification). Auto ID is defined as “the identification of an object with minimal human interaction” (Puckett, 1998). Auto ID has been in existence for some time; in fact, the bar code, the most ubiquitous form of Auto ID, celebrated its 30th year in commercial use in 2004 (Albright, 2004). Barcodes identify items through the encoding of data in various sized bars using a variety of symbologies, or coding methodologies. The most familiar type of barcode is the UPC, or universal product code, which provides manufacturer and product identification. While barcodes have proven to be very useful, and indeed, have become an accepted part of product usage and identity, there are limitations with the technology. Barcode scanners must have line of sight in order to read barcode labels. Label information can be easily compromised by dirt, dust, or rips. Barcodes take up a considerable footprint on product labels. Even the newer barcode symbologies, such as 2D, or two-dimensional, which can store a significant amount of data in a very small space (“Two dimensional…,” 2005) remain problematic. RFID proponents argue that limitations of barcodes are overcome through the use of RFID labeling to identify objects.

RANSAC Feature Based Master-Slave Tracking System for Multi-AGV

2013 ◽  
Vol 404 ◽  
pp. 645-649
Author(s):  
Li Ping Jiang ◽  
Biao Zhang ◽  
Qi Xin Cao ◽  
Chun Tao Leng
Keyword(s):  
Point Cloud ◽  
Control Method ◽  
Average Distance ◽  
Tracking System ◽  
Adaptive Controller ◽  
Laser Range Finder ◽  
Two Dimensional ◽  
Range Finder ◽  
Position Information ◽  
Laser Range

In order to solve the transportation problem in large aircraft components assembly process, an AGV posture synchronization system is built, which utilizes a two-dimensional laser range finder and adaptive control method. Two-dimensional laser range finder is located in the front of AGV to collect real-time point cloud of environment. After tracking AGV section point cloud, we extract straight lines and turning points using the RANSAC algorithm, and estimate the relative posture accordingly. Then adaptive controller processes the position information to achieve master-slave tracking for multi-AGV. In experiment we used three sets of identical AGV; the average distance error was less than 5mm while the angle error was limited within 0.3 °. The results verified the reliability and practicability of our system, which can meet the requirements for transporting large parts.

The Research of Demarcating the Laser Ranging Sensor by Least Squares Method

2014 ◽  
Vol 983 ◽  
pp. 204-207
Author(s):  
Yan Zheng ◽  
Yong Zhang ◽  
Xiao Wang Fan
Keyword(s):  
Surface Roughness ◽  
Least Squares ◽  
Least Squares Method ◽  
Laser Ranging ◽  
Material Surface ◽  
Laser Range Finder ◽  
Range Finder ◽  
Laser Range ◽  
Contact Measurement

Basing on the laser range finder needs calibration used in non-contact measurement the, using the triangle range principle, through the experiment of design of different material, surface roughness, the under the different distance of under the different distance between 40 mm to 60 mm is achieved, the under the different distance, demarcated the laser ranging sensor by least squares method and analyzed the pricesion.

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