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Automated Guided Vehicles by Permanent Magnet Synchronous Motor: Future of In-house Logistics

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Material handling and logistics management that involve transportation of work pieces on production floor are important aspects to manufacturing that affect productivity and efficiency. Tow vehicles that are manually driven are currently used for this purpose. These processes can be better performed through automation. Automated guided vehicle (AGV) is an apt solution. AGVs are unmanned autonomous vehicles that can be programmed to perform versatile tasks. AGVs available in market are imported and hence have high capital cost and increased lead time for spare parts. Proposed AGV is built with a capital cost that is less than half of the existing AGVs. Its design is made indigenously, with most of its parts locally sourced. It can achieve a speed of 0.83 m/s, with a pulling capacity of 1,300 kg. Its rechargeable batteries sustain four hours of continuous operation for one complete discharge. It has been tested and found to effectively replace tow vehicles.
Wydawca
Rocznik
Strony
151--159
Opis fizyczny
Bibliogr. 22 poz., rys., tab.
Twórcy
autor
  • Department of Electrical Engineering, PES University, Bangalore, India
  • Department of Electrical Engineering, PES Institute of Technology, Bangalore, India
  • Department of Electrical Engineering, PES Institute of Technology, Bangalore, India
autor
  • Department of Electrical Engineering, PES University, Bangalore, India
Bibliografia
  • Camara, M. B., Gualous, H., Gustin, F, Berthon, A. and Dakyo, B. (2010). DC/DC Converter Design for Super capacitor and Battery Power Management in Hybrid Vehicle Applications Poly-nomial Control Strategy. IEEE Transactions on Industrial Electronics, 57(2), pp. 587–597.
  • Cao, W. P., Mecrow, B. C., Atkinson, G. J., Bennnett, J. W. and Atkinson, D. J. (2012). Overview of Electric Motor Technologies Used for More Aircraft (MEA). IEEE Transactions on Industrial Electronics, 59(2), pp. 803–811.
  • Dougal, R. A., Liu, S. and White, R.E. (2002). Power and Life Extension of Battery-Ultracapacitor Hybrids. IEEE Transactions on Components and Packaging Technologies, 25(1), pp. 120–131.
  • Evans, J., Krishnamurthy, B., Barrows, B., Skewis, T. and Lumelsky, V. (1992). ‘Handling Real-World Motion Planning: A Hospital Transport Robot. IEEE Control Systems, 12(1), pp. 15–19.
  • Frost and Sullivan (2013) Automation Market to Reach USD 2000 Million by 2016 - Frost and Sullivan, CEW India Publication, Feb 2013
  • Fujimoto, T., Ota, J, Arai, T., Ueyama, T. and Nishiyama, T. (2001). Semi-guided navigation of AGV through iterative learning. In Intelligent Robots and Systems, 2001. Proceedings. 2001 IEEE/RSJ International Conference on, volume 2, pp. 968–973. IEEE.
  • Graf, B., Hans, M. and Schraft, R. D. (2004). Care-O-bot II—Development of a Next Generation Robotic Home Assistant. Autonomous Robots, 16(2), pp. 193–205.
  • Grisetti, G., Kümmerle, R., Stachniss, C. and Burgard, W. (2010). A tutorial on graph-based SLAM. The IEEE Intelligent Transportation Systems Magazine, 2(4), pp. 31–43.
  • Jensfelt, P. and Kristensen, S. (2001). Active Global Localization for a Mobile Robot Using Multiple Hypothesis Tracking. IEEE Transactions on Robotics and Automation, 17(5), pp. 748–760.
  • Koch, R., May, S., Murmann, P. and Nüchter, A. (2017). Identification of transparent and specular reflective material in laser scans to discriminate affected measurements for faultless robotic SLAM. Robotics and Autonomous Systems, 87, pp. 296–312.
  • McDonald, J., Kaess, M., Cadena, C., Neira, J. and Leonard, J. J. (2013). Real-Time 6-DOF Multi-Session Visual SLAM Over Large-Scale Environments. Robotics and Autonomous Systems, 61(10), pp. 1144–1158.
  • Miller, R. K., Stewart, D. G., Brockman, W. H. and Skaar, S. B. (1994). A Camera Space Control System for an Automated Forklift. IEEE Transactions on Robotics and Automation, 10(5), pp. 710–716, doi: 10.1109/70.326575
  • Ortuzar, M, Moreno, J. and Dixon, J. (2007). Ultracapacitor-Based Auxiliary Energy System for an Electric Vehicle: Implementation and Evaluation, IEEE Transactions on Industrial Electronics, 54(4), pp. 2147–2156.
  • Pang, Y., De La Cruz, A. L. and Lodewijks, G. (2008). Bipolar magnetic positioning system for automated guided vehicles. Intelligent Vehicles Symposium, 2008 IEEE, pp. 883–888. IEEE.
  • Patel, D. D. and Salameh, Z. M. Characterization of GP30EVLF 30 Ah Lithium Iron Phosphate Battery Cells. Power & Energy Society General Meeting, 2015 IEEE, pages 1–5. IEEE, 2015.
  • Pavkovic´, D., Lobrovic´, M., Hrgetic´, M. and Komljenovic´, A. (2014) A Design of DC Bus Control System for EVs Based on Battery/Ultracapacitor Hybrid Energy Storage. In Electric Vehicle Conference (IEVC), 2014 IEEE International, pages 1–8. IEEE.
  • Raghavendra Rao, A., & Mahesh, M. (2018). Analysis of the energy and safety critical traction parameters for elevators. EPE Journal, 28(4), 169-181.
  • Takahashi, M., Suzuki, T., Shitamoto, H., Moriguchi, T. and Yoshida, K. (2010). Developing a Mobile Robot for Transport Applications in the Hospital Domain, Robotics and Autonomous Systems, 58(7), pp. 889–899.
  • Tasaki, R., Kitazaki, M., Miura, J. and Terashima, K. (2015). Prototype Design of Medical Round Supporting Robot ‘Terapio,’ in Proceedings of IEEE IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, pp. 829–834.
  • Ullrich, G. (2015). Automated Guided Vehicle Systems: A Primer with Practical Applications. Berlin: Springer, pp. 38–40, 2nd revised edition
  • Vivaldini, K. C. T. et al. (2010). Robotic forklifts for intelligent warehouses: Routing, path planning, and auto-localization. 2010 IEEE International Conference on Industrial Technology, Vina del Mar, pp.1463–1468. doi: 10.1109/ICIT.2010.
  • Wang, K., Zhu, Z. Q., Grzegorz Ombach, Koch, M., Zhang, S. and Xu, J. (2014). Electromagnetic Performance of an 18-Slot/10-Pole Fractional-Slot Surface-Mounted Permanent-Magnet Machine. IEEE Transactions on Industry Applications, 50(6), pp. 3685–3696.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-589217ca-9bc5-400d-ac66-d7e693c1bc4d
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