RFID Based Object Localization System Using Ceiling Cameras with Particle Filter

Kamol, P.; Nikolaidis, Stefanos; Ueda, Ryuichi; Arai, Tamio

doi:10.1109/fgcn.2007.194

Cited by 33 publications

(22 citation statements)

References 12 publications

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“…RFID can overcome the deficiencies of QR Code because RFID has the following advantages [11][12][13][14]: non-contactable, identify multi-target at the same time, high speed and far distance, etc. RFID system mainly includes three parts: antenna, reader, and RFID tag, shown in Fig.…”

Section: B Rfid Information Representation Modelmentioning

confidence: 99%

Multi-pattern information representation and acquisition in intelligent space

Xue

Tian

Zhou

2011

2011 Chinese Control and Decision Conference (CCDC)

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Intelligent space has changed the one to one occupying mode between robot and sensing devices in traditional pattern, making the computational resources and all kinds of devices tend to be public and sharing. In order to make full use of the different services and resources, a new information representation method based on modified JDL is presented in the paper, which can represent the information from QR Code, RFID in a uniform format, and realize information interoperability and sharing. Due to the strong computational ability of intelligent space, the information service in the intelligent space is not limited in the original signal level, but also the deeper understanding through data fusion. A multi-pattern acquisition model based on the distributed data fusion tree is built in the paper aiming to realize multi-class, multi-level processing to the distributed sensor data. The example demonstrates that the new model proposed in the paper can improve the positioning precision of robot and targets greatly, and the search efficiency and success rate are also better than traditional pattern.

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Section: B Rfid Information Representation Modelmentioning

confidence: 99%

Multi-pattern information representation and acquisition in intelligent space

Xue

Tian

Zhou

2011

2011 Chinese Control and Decision Conference (CCDC)

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“…Kulyukin et al (2004) and Kulyukin et al (2006) used the passive RFID system with the LRF for guiding visually impaired. Chae and Han (2005) and Kamol et al (2007) used vision information to improve the position estimation performance. and used active RFID tags that have LEDs on it.…”

Section: Rfid Systems For Indoor Mobile Robotsmentioning

confidence: 99%

Improving Position Estimation of the RFID Tag Floor Localization with Multiple Recognition Ranges

Park¹,

Lee²,

Kim³

et al. 2011

Advanced Radio Frequency Identification Design and Applications

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This chapter introduces the RFID tag floor localization method with multiple recognition ranges and its mathematical formulation to improve position estimation accuracy. Using the multiple recognition ranges of RFID reader, the reader can obtain more information about the distances to the tags on the tag floor. The information is used to improve the position estimation performance. At first, this chapter reviews the RFID tag floor localization method with single recognition range for mobile robots (Park et al., 2010) and The performance measure based on the position estimation error variance for the localization method. For the second, this paper extends the mathematical formulation of the localization method and the performance measure for the case of multiple recognition ranges. This work is related to the previous work (Park et al., 2009) that used multiple powers to improve position estimation performance. However, previous work lacks analysis and mathematical formulation of general RFID tag recognition models. We extend the mathematical formulation and the analysis of the single recognition range RFID tag floor localization method (Park et al., 2010) to the multiple recognition range case. Then the minimum error variance of multiple recognition range is introduced as a lower bound of position estimation error variance. Finally, it presents performance improvement of proposed localization method via the Monte-Carlo simulation and simple experiments. The analysis for the simulation and experimental results and the consideration for real application will be given. This chapter is organized as follows; This section discusses sensor systems used in the mobile robot localization. Then the advantages of the RFID systems as sensor systems for localization are discussed and the researches on the systems are reviewed. Section 2 introduces the RFID tag floor localization, its mathematical formulation and its performance index. Section 3 represents the motivation of introducing the use of multiple recognition ranges for the RFID tag floor localization method, and extend the mathematical formulation and the error variance for the multiple recognition range case. Section 4 conducts the Monte-Carlo simulation to show the improvement of the position estimation performance when the multiple recognition range is used. Section 5 represents experimental results that support the simulation results. In Section 6, the minimum error variance (Park et al., 2010) as a lower bound of error variance is extended to the multiple recognition range case. Section 7 gives the conclusions, discussions and tasks for the further researches.

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“…There are two kinds of antennas: linear polarized antenna (LPA) and circular polarized antenna (CPA), which looks similar in appearance, as shown in Figure 3 (on the right). The LPA is installed on the robot because the narrow recognition angle of LPA can guarantee the correct time sequence when the robot read the tags (as discussed elsewhere [12][13][14][15][16]). …”

Section: ) Qr Code Information Representation Modelmentioning

confidence: 99%

Building an Intelligent Home Space for Service Robot Based on Multi-Pattern Information Model and Wireless Sensor Networks

Lu¹,

Tian²,

Zhou³

et al. 2012

ICA

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This paper is concerned with constructing a prototype intelligent home environment for home service robot. In this environment, multi-pattern information can be represented by some intelligent artificial marks. Light-packs service robots can provide reliable and intelligent service by interacting with the environment through the wireless sensor networks. The intelligent space consists the following main components: smart devices with intelligent artificial mark; home server that connects the smart device and maintains the information through wireless sensor network; and the service robot that perform tasks in collaboration with the environment. In this paper, the multi-pattern information model is built, the construction of wireless sensor networks is presented, the smart and agilely home service is introduced. Fi-nally, the future direction of intelligent space system is discussed.

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RFID Based Object Localization System Using Ceiling Cameras with Particle Filter

Cited by 33 publications

References 12 publications

Multi-pattern information representation and acquisition in intelligent space

Multi-pattern information representation and acquisition in intelligent space

Improving Position Estimation of the RFID Tag Floor Localization with Multiple Recognition Ranges

Building an Intelligent Home Space for Service Robot Based on Multi-Pattern Information Model and Wireless Sensor Networks

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