Global Posture Estimation of a Tour-guide Robot using RFID and Laser Scanning Measurements

Lin, Hung-Hsing; Tsai, Ching‐Chih; Chang, Hsu-Yang

doi:10.1109/iecon.2007.4460081

Cited by 6 publications

(4 citation statements)

References 12 publications

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“…Again, in Smart Environment applications [56], RFID robots are employed to perform as shopping assistants [57] or tour-guide in museums or exhibitions [58]. Since such scenarios are typically multi-floor, e.g., shopping malls or museums, reference tags can be easily installed to allow the recognition of the floor/room through the association of the detected EPC with a proper database.…”

Section: Rfid Vehicle Localization a Application Scenariosmentioning

confidence: 99%

“…Exteroceptive sensors can have different natures: cameras, i.e., computer vision systems, [55], [74], [102]- [104], Laser Range Finders [58], [105], [106], Wi-Fi and other RF systems [107]- [108], ultrasounds [109], [110], or hybrid solutions [52], [111]. The introduction of a second exteroceptive system in addition to the RFID system does not imply that proprioceptive sensors must be removed.…”

Section: Rfid Sensor-fusion With Additional Exteroceptive Sensorsmentioning

confidence: 99%

“…In [58], a sensor-fusion tracking system comprising an active RFID system, an odometer and a laser scanner was proposed. By employing the odometer data from the driving wheels and the laser scanning measurements of the robot surroundings, a localization algorithm based on Extended Information Filter (EIR) is proposed to continuously keep track of the robot poses at slow speeds.…”

Section: B Rfid Sensor-fusion With Laser Range Findermentioning

confidence: 99%

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A Survey on Indoor Vehicle Localization Through RFID Technology

2021

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This paper presents a state-of-the-art analysis on the methods suitable for vehicle indoor localization and exploiting the RFID (Radio Frequency IDentification) technology. The survey describes three main categories of vehicle localization systems: (i) solutions exploiting only the RFID technology, (ii) sensor-fusion techniques combining data from RFID systems and proprioceptive sensors, and (iii) sensorfusion techniques combing RFID data with those of other exteroceptive sensors in addition to the RFID system itself. For each method, implementation and methodological details are discussed, by highlighting the applied RFID technology, namely passive HF-RFID, passive UHF-RFID, or any other RFID system. Also, the employed RFID parameters, i.e., tag EPC, RSSI or backscattered phase, are discussed. The survey focuses on the achievable localization performance, also accounting for infrastructure-deployment costs together with complexity and maintenance overhead. Positioning, tracking, navigation and simultaneous localization and mapping (SLAM) issues are here considered. The analysis highlights pros and cons of each method, together with the main challenges and perspectives of RFID-based solutions for vehicle localization.

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Section: Rfid Vehicle Localization a Application Scenariosmentioning

confidence: 99%

Section: Rfid Sensor-fusion With Additional Exteroceptive Sensorsmentioning

confidence: 99%

Section: B Rfid Sensor-fusion With Laser Range Findermentioning

confidence: 99%

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A Survey on Indoor Vehicle Localization Through RFID Technology

2021

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“…Nowadays, there are not many manufacturers who offer tags with sensor functionality, and most often, solutions are active or semipassive [6], [7]. However, to take full advantage of the RFID technology in terms of device autonomy, small form factor, and low price, passive tags have to be targeted.…”

Section: Introductionmentioning

confidence: 99%

An Ultralow-Power Mixed-Signal Back End for Passive Sensor UHF RFID Transponders

Rodríguez-Rodríguez

Delgado‐Restituto

Masuch

et al. 2012

IEEE Trans. Ind. Electron.

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This paper describes the design of mixed-signal back end for an ultrahigh-frequency sensor-enabled radio-frequency identification transponder in full compliance with the Electronic Product Code Class-1 Generation-2 protocol, defined in the standard ISO 18000-6C. The chip, implemented in a low-cost 0.35-µm CMOS technology process, includes a baseband processor, an analog-to-digital converter (ADC) to digitize the signal acquired from the external sensor, and some auxiliary circuitry for voltage regulation and reference generation. The proposed solution uses two different supply voltages, one for the processor and the other for the mixed-signal circuitry, and defines a novel communication protocol between both blocks so that analog readouts are minimally affected by the digital activity of the tag. The whole system was first functionally validated by exhaustively testing with external dc power supplies ten prototype samples, and then, the two main blocks, processor, and ADC were individually tested to assess their performance limits. Regarding the baseband processor, experiments were performed toward the calculation of its packet error rate (PER) under two typical biasing configurations of passive tags, using either crude clamps or regulators. It was found that the regulated biasing outperforms the clamping solution and obtains a PER of 3 × 10 −3 with a supply voltage of 0.75 V. The current consumption of the processor during the reception and response to a Read command at maximum backward rate is only 2.2 µA from a 0.9-V supply. Regarding the ADC, it is a 10-b successive approximation register converter which obtains 9.41 b of effective resolution at 2-kS/s sampling frequency with a power consumption of 250 nW, including the dissipation of a current generation cell and the clock generation circuitry, from 1-V supply.

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