Fault detection algorithm for automatic guided vehicle based on multiple positioning modules

Pratama, Pandu Sandi; Setiawan, Yuhanes Dedy; Kim, Dae Hwan; Jung, Youngae; Kim, Hak Kyeong; Jeong, Sang Kwun; Jeong, Jin Il

doi:10.1109/icacci.2014.6968511

Cited by 5 publications

(4 citation statements)

References 9 publications

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“…Para a detecção de falhas que possam ocorrer durante a execução de tarefas que estajam a ser efectuadas pelos AGVs, Pandu Sandi Pratama et al [33] fazem uso de uma técnica previamente usada, presente em vários casos na secção 2.1, referente à localização. Esta técnica corrresponde ao uso de um filtro de Kalman, mais concretamente, de um Extended Kalman Filter (EKF).…”

Section: Detecção De Falhasunclassified

Analysis of AGV indoor tracking supported by IMU sensors in intra-logistics process in automotive industry

Grilo

Costa

Figueiras

et al. 2021

2021 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC)

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têm o direito, perpétuo e sem limites geográficos, de arquivar e publicar esta dissertação através de exemplares impressos reproduzidos em papel ou de forma digital, ou por qualquer outro meio conhecido ou que venha a ser inventado, e de a divulgar através de repositórios científicos e de admitir a sua cópia e distribuição com objetivos educacionais ou de investigação, não comerciais, desde que seja dado crédito ao autor e editor.Este documento foi gerado utilizando o processador (pdf)L A T E X, com base no template "novathesis" [1] desenvolvido no Dep. Informática da FCT-NOVA [2].[1] https://github.com/joaomlourenco/novathesis [2] http://www.di.fct.unl.pt

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Section: Detecção De Falhasunclassified

Analysis of AGV indoor tracking supported by IMU sensors in intra-logistics process in automotive industry

Grilo

Costa

Figueiras

et al. 2021

2021 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC)

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“…Zacharaki et al [19] discussed the safety problem and the risk assessment techniques in the field of human-robot interaction. Pratama et al [20] presented a fault detection algorithm to analyze the sensors and motors of AGVs based on multiple positioning modules. Witczak et al [21] concentrated on a strategy based on a fault-tolerant control framework and improved the sustainability and flexibility of the warehouse AGV system.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Optimization of the Robotic Mobile Fulfillment Systems Considering Congestion

Chi

Wang

et al. 2021

Applied Sciences

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With the development of the social economy and the improvement of the consumption concept, a new business model combining offline and online has been promoted. The warehousing system is one of the important links of commodity production and circulation, which involves storage, sorting, and distribution. It has a significant impact on the operation cost and the efficiency of the whole logistics system. The progress of robot technology, the Internet of things, and artificial intelligence technology promotes the automation and intelligence of storage systems. The Robotic Mobile Fulfillment Systems (RMFS), which takes the automatic guided vehicles (AGVs) as the way of handling and picking, greatly improves the space utilization, operation efficiency, and flexibility of the system. This paper studies the RMFS with fixed shelves and establishes the performance evaluation model of the picking system considering the AGVs congestion by establishing the queuing network. The effectiveness of the model is verified by simulation, and the optimization of system parameter configuration is further discussed according to the experimental data.

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“…It should be advised that although EKF 1 is driven by all seven INS measurements, only six residuals can be generated. The reason is that the mean rear wheel speed, instead of two separate speeds, is used in the measurement update of the EKF 1, which can be seen in (23).…”

Section: Residualmentioning

confidence: 99%

“…Each observer is driven by all inputs and all but one output to diagnose a sensor fault. Additionally, in the very recent work from [21][22][23], the EKF is used to calculate the measurement probability distribution of the intelligent vehicle position for nonlinear models driven by Gaussian noise. Using the probability distribution of innovation obtained from EKF, it is possible to test if the measured data are fit with the models.…”

Section: Introductionmentioning

confidence: 99%

Design of a Fault Detection and Isolation System for Intelligent Vehicle Navigation System

Huang

2015

International Journal of Navigation and Observation

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This paper deals with the design of a fault detection and isolation (FDI) system for an intelligent vehicle, a vehicle equipped with advanced driver assistance system (ADAS). The ADASs are outfitted with sensors for acquiring various information about the vehicle and its surroundings. Since these sensors are sensitive to faults, an efficient FDI system should be developed. The designed FDI system is comprised of three parts: a detection part, a decision part, and a fault management part. The detection part applies a generalized observer scheme (GOS). In the GOS, there is bank of extended Kalman filters (EKFs), each excited by all except one sensor measurement. The residual generated from the measurement update of each EKF is therefore sensitive to all sensor faults but one. This way, the fault sensitivity pattern of the residual makes it possible to detect a fault and locate the faulty sensor. The designed FDI system has been implemented and tested off-line with actual experiment data. Good results have been obtained with diagnosing individual sensor faults and outputting fault-free vehicle states.

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Fault detection algorithm for automatic guided vehicle based on multiple positioning modules

Cited by 5 publications

References 9 publications

Analysis of AGV indoor tracking supported by IMU sensors in intra-logistics process in automotive industry

Analysis of AGV indoor tracking supported by IMU sensors in intra-logistics process in automotive industry

Analysis and Optimization of the Robotic Mobile Fulfillment Systems Considering Congestion

Design of a Fault Detection and Isolation System for Intelligent Vehicle Navigation System

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