An indoor mobile robot positioning system based on radio-frequency identification

2017 ◽  
Vol 50 (3) ◽  
pp. 313-322 ◽  
Author(s):  
Jiansheng PENG ◽  
Jian MIAO ◽  
Qingjin WEI ◽  
Zhenwu WAN ◽  
Yiyong HUANG ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Positioning System ◽  
Indoor Mobile Robot ◽  
Robot Positioning ◽  
Frequency Identification

scholarly journals A robust mobile robot indoor positioning system based on Wi-Fi

2020 ◽  
Vol 17 (1) ◽  
pp. 172988141989666 ◽  
Author(s):  
Wei Cui ◽  
Qingde Liu ◽  
Linhan Zhang ◽  
Haixia Wang ◽  
Xiao Lu ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Principal Component ◽  
Indoor Positioning ◽  
Positioning System ◽  
Infrared Sensors ◽  
Positioning Systems ◽  
Indoor Mobile Robot ◽  
Robot Positioning ◽  
Learning Machine ◽  
Noisy Measurements

Recently, most of the existing mobile robot indoor positioning systems (IPSs) use infrared sensors, cameras, and other extra infrastructures. They usually suffer from high cost and special hardware implementation. In order to address the above problems, this article proposes a Wi-Fi-based indoor mobile robot positioning system and designs and develops a robot positioning platform based on the commercial Wi-Fi devices, such as Wi-Fi routers. Furthermore, a robust principal component analysis-based extreme learning machine algorithm is proposed to address the issue of noisy measurements in IPSs. Real-world robot indoor positioning experiments are extensively carried out and the results verify the effectiveness and superiority of the proposed system.

Design and Robust Recognition of Omnidirectional Landmarks for Indoor Mobile Robot Positioning

2013 ◽  
Author(s):  
Hanyu Liu ◽  
Xu Zhong ◽  
Yu Zhou
Keyword(s):  
Mobile Robot ◽  
Recognition Algorithm ◽  
Positioning System ◽  
Contour Analysis ◽  
Landmark Recognition ◽  
Black And White ◽  
Indoor Mobile Robot ◽  
Robot Positioning ◽  
Robust Recognition ◽  
Landmark Model

In this paper, we present an omnidirectional artificial landmark model and a robust artificial landmark recognition algorithm for indoor mobile robot positioning. The landmark model encodes identities with nested circles in black and white, which provides stable edge response and enables strong tolerance to various lighting conditions and perspective distortions. The corresponding positioning system uses a single upward-facing webcam as the vision sensor to capture landmarks. To address the effect of the lighting and sensing noise, the topological contour analysis is applied to detect landmarks, and the dynamic illumination adjustment is used to assist landmark recognition. Based on the landmark recognition, the absolute position of the camera in the environment is estimated using a trilateration algorithm. The landmark model and positioning system are tested with a mobile robot in a real indoor environment. The results show that the purposed technique provides autonomous indoor positioning for mobile robots with high robustness and consistency.

BUILDING MAP AND POSITIONING SYSTEM FOR INDOOR ROBOT BASED ON PLAYER

2011 ◽  
Vol 08 (04) ◽  
pp. 281-290
Author(s):  
BIN WANG ◽  
WEI LU ◽  
BIN KONG
Keyword(s):  
Mobile Robot ◽  
Positioning System ◽  
Map Building ◽  
Adaptive Monte Carlo ◽  
Indoor Mobile Robot ◽  
Robot Positioning ◽  
Positioning Method ◽  
Dynamic Map ◽  
Slam Algorithm ◽  
Number Of Particles

In this paper, we have proposed a map-building and positioning method for an indoor mobile robot based on the open source platform Player. First, the DP-SLAM algorithm is transplanted to the Player and used to build the dynamic offline map. This would reduce the errors and constraints caused by manual map building. Second, the KLD-Sampling Adaptive Monte Carlo Locating (KLD-AMCL) algorithm is introduced to reduce the number of particles required in locating. Meanwhile, higher accuracy of localization is achieved through calculating the MLE and the real posterior KL distance. Finally, an indoor mobile robot positioning system is built by combining the Player platform, dynamic map building and KLD-AMCL algorithm. Experimental results show that the proposed system has better environmental adaptability and higher positioning accuracy.

The Automatic Positioning System of Coke Oven Locomotive Based on Radio Frequency Identification and Image Processing

2012 ◽  
Vol 588-589 ◽  
pp. 822-825
Author(s):  
Yong Tao Zhang ◽  
Lan Wu ◽  
Jing Dong Bo ◽  
Qing Ping Li ◽  
Jing Xuan Zhang
Keyword(s):  
Image Processing ◽  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Technology Use ◽  
Design Method ◽  
Coke Oven ◽  
Video Camera ◽  
Positioning System ◽  
Accurate Identification ◽  
Frequency Identification

Proposed the design method that separation of coking chamber’s number identification and accurate position. Researching new coke oven locomotive positioning system application of radio frequency identification and image processing technology, use radio frequency identification technology on accurate identification of coking chamber’s number, and then use the video camera to identify door image and its center point for accurate positioning of coke oven locomotive.

Design of Indoor Mobile Robot Positioning System Based on STC12C5616AD MCU and nRF24L01

2012 ◽  
Vol 11 (1) ◽  
pp. 429-432
Author(s):  
Enxiu Shi ◽  
Jiali Yang ◽  
Jun Li ◽  
Xian Wang
Keyword(s):  
Mobile Robot ◽  
Positioning System ◽  
Indoor Mobile Robot ◽  
Robot Positioning

Auto-localization system for indoor mobile robot using RFID fusion

Robotica ◽  
2014 ◽  
Vol 33 (9) ◽  
pp. 1899-1908 ◽  
Author(s):  
A. Abdelgawad
Keyword(s):  
Mobile Robot ◽  
Radio Frequency Identification ◽  
Accurate Estimation ◽  
Localization System ◽  
Accurate Localization ◽  
Indoor Mobile Robot ◽  
Current Location ◽  
Frequency Identification ◽  
Passive Rfid ◽  
Estimated Error

SUMMARYAutonomous mobile robots need accurate localization techniques to perform assigned task. Radio Frequency Identification Technology (RFID) has become one of the main means to construct a real-time localization system. Localization techniques in RFID rely on accurate estimation of the read range between the reader and the tags. This paper proposes an auto-localization system for indoor mobile robot using passive RFID. The proposed system reads any three different RFID tags which have a known location. The current location can be estimated using the Time Difference of Arrival (TDOA) scheme. In order to improve the system accuracy, the proposed system fuses the TDOA scheme for the three tags. A Kalman filter is used to minimize the estimated error and predict the next location. The simulation results validate the proposed framework.

scholarly journals Sistem Keamanan Sepeda Motor Menggunakan GPS Dan Radio Frequency Identification (RFID) Berbasis Arduino

2021 ◽  
Vol 19 (2) ◽  
pp. 47-53
Author(s):  
Herwin Simanjuntak ◽  
Rully Pramudita ◽  
Nadya Safitri
Keyword(s):  
Radio Frequency ◽  
Global Positioning System ◽  
Radio Frequency Identification ◽  
Safety System ◽  
Motor Vehicles ◽  
Positioning System ◽  
Security Systems ◽  
Motorcycle Safety ◽  
Global Positioning ◽  
Frequency Identification

Abstract- At this time motorcycle theft cases are still often occur plus the increasing use of motorcycle vehicles, motorcycle theft is caused by the lack of a security system on the ignition which only uses keys and key covers, where security systems like this have been understood mostly motorcycle thieves, the necessity of a motorcycle safety system is needed. To overcome this, a Motorcycle Safety System was made using Arduno-based GPS and Radio Frequency Identification (RFID) to prevent and facilitate the recovery of stolen motor vehicles. The results of this study, the system is made using the Global Positioning System (GPS) as a tool to detect the location of motorcycles, and smart key contacts are added using RFID, SMS gateway and DC-DC Converter.

Sign in / Sign up

Export Citation Format

Share Document