New hybrid vision-based control approach for automated guided vehicles
Само за регистроване кориснике
2013
Чланак у часопису (Објављена верзија)
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Automated guided vehicles (AGVs) are a common choice made by many companies for material handling (MH) in manufacturing systems. AGV-based internal transport of raw materials, goods, and parts is becoming improved with advances in technology. Demands for fast, efficient, and reliable transport imply the usage of the flexible AGVs with onboard sensing and special kinds of algorithms needed for daily operations. So far, the majority of these transport solutions have not considered the modern techniques for visual servoing, monocular SLAM, and consequently, the usage of camera as onboard sensor for AGVs. In this research, a new hybrid control of AGV is proposed. The main control algorithm consists of two independent control loops: position-based control (PBC) for global navigation and image based visual seroving (IBVS) for fine motions needed for accurate steering towards loading/unloading point. By separating the initial transportation task into two parts (global navigation towards the g...oal pose near the loading/unloading point and fine motion from the goal pose to the loading/unloading point), the proposed hybrid control bypasses the need for artificial landmarks or accurate map of the environment. The state estimation of the robot pose is determined in terms of monocular SLAM, via extended Kalman filter coupled with feedforward neural network-the neural extended Kalman filter (NEKF). NEKF is used to model unknown disturbances and to improve the robot state transition model. The integration of the new hybrid control and NEKF has been tested in laboratory with the mobile robot and simple camera. Experimental results present the effectiveness of the proposed hybrid control approach.
Кључне речи:
Neural network / Monocular SLAM / Image-based visual servoing / Extended Kalman filter / Epipolar geometry / Automated guided vehicleИзвор:
International Journal of Advanced Manufacturing Technology, 2013, 66, 1-4, 231-249Издавач:
- Springer London Ltd, London
Финансирање / пројекти:
- Иновативни приступ у примени интелигентних технолошких система за производњу делова од лима заснован на еколошким принципима (RS-MESTD-Technological Development (TD or TR)-35004)
DOI: 10.1007/s00170-012-4321-y
ISSN: 0268-3768
WoS: 000316574300019
Scopus: 2-s2.0-84875479536
Колекције
Институција/група
Mašinski fakultetTY - JOUR AU - Miljković, Zoran AU - Vuković, Najdan AU - Mitić, Marko AU - Babić, Bojan PY - 2013 UR - https://machinery.mas.bg.ac.rs/handle/123456789/1691 AB - Automated guided vehicles (AGVs) are a common choice made by many companies for material handling (MH) in manufacturing systems. AGV-based internal transport of raw materials, goods, and parts is becoming improved with advances in technology. Demands for fast, efficient, and reliable transport imply the usage of the flexible AGVs with onboard sensing and special kinds of algorithms needed for daily operations. So far, the majority of these transport solutions have not considered the modern techniques for visual servoing, monocular SLAM, and consequently, the usage of camera as onboard sensor for AGVs. In this research, a new hybrid control of AGV is proposed. The main control algorithm consists of two independent control loops: position-based control (PBC) for global navigation and image based visual seroving (IBVS) for fine motions needed for accurate steering towards loading/unloading point. By separating the initial transportation task into two parts (global navigation towards the goal pose near the loading/unloading point and fine motion from the goal pose to the loading/unloading point), the proposed hybrid control bypasses the need for artificial landmarks or accurate map of the environment. The state estimation of the robot pose is determined in terms of monocular SLAM, via extended Kalman filter coupled with feedforward neural network-the neural extended Kalman filter (NEKF). NEKF is used to model unknown disturbances and to improve the robot state transition model. The integration of the new hybrid control and NEKF has been tested in laboratory with the mobile robot and simple camera. Experimental results present the effectiveness of the proposed hybrid control approach. PB - Springer London Ltd, London T2 - International Journal of Advanced Manufacturing Technology T1 - New hybrid vision-based control approach for automated guided vehicles EP - 249 IS - 1-4 SP - 231 VL - 66 DO - 10.1007/s00170-012-4321-y ER -
@article{ author = "Miljković, Zoran and Vuković, Najdan and Mitić, Marko and Babić, Bojan", year = "2013", abstract = "Automated guided vehicles (AGVs) are a common choice made by many companies for material handling (MH) in manufacturing systems. AGV-based internal transport of raw materials, goods, and parts is becoming improved with advances in technology. Demands for fast, efficient, and reliable transport imply the usage of the flexible AGVs with onboard sensing and special kinds of algorithms needed for daily operations. So far, the majority of these transport solutions have not considered the modern techniques for visual servoing, monocular SLAM, and consequently, the usage of camera as onboard sensor for AGVs. In this research, a new hybrid control of AGV is proposed. The main control algorithm consists of two independent control loops: position-based control (PBC) for global navigation and image based visual seroving (IBVS) for fine motions needed for accurate steering towards loading/unloading point. By separating the initial transportation task into two parts (global navigation towards the goal pose near the loading/unloading point and fine motion from the goal pose to the loading/unloading point), the proposed hybrid control bypasses the need for artificial landmarks or accurate map of the environment. The state estimation of the robot pose is determined in terms of monocular SLAM, via extended Kalman filter coupled with feedforward neural network-the neural extended Kalman filter (NEKF). NEKF is used to model unknown disturbances and to improve the robot state transition model. The integration of the new hybrid control and NEKF has been tested in laboratory with the mobile robot and simple camera. Experimental results present the effectiveness of the proposed hybrid control approach.", publisher = "Springer London Ltd, London", journal = "International Journal of Advanced Manufacturing Technology", title = "New hybrid vision-based control approach for automated guided vehicles", pages = "249-231", number = "1-4", volume = "66", doi = "10.1007/s00170-012-4321-y" }
Miljković, Z., Vuković, N., Mitić, M.,& Babić, B.. (2013). New hybrid vision-based control approach for automated guided vehicles. in International Journal of Advanced Manufacturing Technology Springer London Ltd, London., 66(1-4), 231-249. https://doi.org/10.1007/s00170-012-4321-y
Miljković Z, Vuković N, Mitić M, Babić B. New hybrid vision-based control approach for automated guided vehicles. in International Journal of Advanced Manufacturing Technology. 2013;66(1-4):231-249. doi:10.1007/s00170-012-4321-y .
Miljković, Zoran, Vuković, Najdan, Mitić, Marko, Babić, Bojan, "New hybrid vision-based control approach for automated guided vehicles" in International Journal of Advanced Manufacturing Technology, 66, no. 1-4 (2013):231-249, https://doi.org/10.1007/s00170-012-4321-y . .