Have a personal or library account? Click to login
Study Regarding the Autonomous Mobile Platforms Used in Industry Cover

Study Regarding the Autonomous Mobile Platforms Used in Industry

Open Access
|Dec 2020

References

  1. 1. Oltean S.E., Mobile Robot Platform with Arduino Uno and Raspberry Pi for Autonomous Navigation.
  2. 2. Radosław C., Marcin B., Indoor vehicle tracking with a smart MEMS sensor.
  3. 3. Chernousko F.L., Locomotion Principles for Mobile Robotic Systems.
  4. 4. Mănoiu O.S., Nițulescu M., Locomotion Over Common Types of Obstacles for a Legged Mobile Robot.
  5. 5. Peng T., Qian J., Zi B., Liu J., Wang X., Mechanical Design and Control System of an Omnidirectional Mobile Robot for Material Conveying
  6. 6. Tomas B. Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems (Third Edition). Xi’an: Xi’an Jiaotong University Press; 2012.
  7. 7. SIEGWART R., NOURBAKHSH I.R., Introduction to Autonomous Mobile Robots
  8. 8. F.G. Rossomando, C.M. Soria, Identification and control of nonlinear dynamicsof a mobile robot in discrete time using an adaptive technique based onneural PID, Int. J. Neural Comput. Appl. (2015) 1179–1191.10.1007/s00521-014-1805-8
  9. 9. S.E. Oltean, M. Dulău, R. Puskas, Position control of robotino mobile robotusing fuzzy logic, IEEE International Conference on Automation Quality andTesting Robotics (AQTR), Romania (2010)10.1109/AQTR.2010.5520855
  10. 10. A.Sheikhlar, A. Fakharian, A. Adhami-Mirhosseini, Fuzzy adaptive PI controlof omni-directional mobile robot, 13th Iranian Conference on Fuzzy Systems(IFSC), Iran (2013) 1–4.10.1109/IFSC.2013.6675667
  11. 11. Masmoudi M.S., Krichen N., Masmoudi M., Derbel N., Fuzzy logic controllers design for omnidirectional mobile robotnavigation
  12. 12. C. Treesatayapun, A.C. Guzman-Carballido, Linearization based on Fuzzy RulesEmulated Networks for nonaffine discrete-time systems controller, TENCON2009 – IEEE Region 10 Conference, TENCOM, Singapore (2009) 1–6.10.1109/TENCON.2009.5395964
  13. 13. Breaz R., Racz G., Using the modern CNC controllers capabilities for estimating the machining forces during the milling process, MATEC Web Conf. Volume 137, 2017, Modern Technologies in Manufacturing (MTeM 2017 - AMaTUC), Cluj-Napoca, 2017, https://doi.org/10.1051/matecconf/20171370400310.1051/matecconf/201713704003
  14. 14. Breaz R., Bologa O., Racz G., Selecting between CNC milling, robot milling and DMLS processes using a combined AHP and fuzzy approach, published in Procedia Computer Science, ISSN: 1877-0509, pp. 796-803, https://doi.org/10.1016/j.procs.2017.11.43910.1016/j.procs.2017.11.439
  15. 15. Racz, S.-G, Breaz, R.-E., Cioca, L.-I., Hazards That Can Affect CNC Machine Tools during Operation—An AHP Approach. Safety 2020, 6, 10. SAFETY, Volume: 6, Issue: 1, Article Number: 10, 2020, DOI: 10.3390/safety6010010, jurnal indexat Clarivate Analytics (ESCI)10.3390/safety6010010
  16. 16. Breaz, R. E., Bologa, O. C., Racz, G. S., Oleksik, V., Motion Control Systems for Machine Tools – a Mechatronic Approach by Means of Simulation, IEEE International Symposium on Industrial Electronics, June 30 – July 2, 2008, Cambridge, pp. 2072-2077, ISBN 978-1-4244-1666-0, IEEE Catalog Number: CFP08ISI-CDR, Library of Congress: 2007936380
  17. 17. Tera, M, Breaz, R.E., Bologa, O., Racz, G., Using a CNC Milling Machine for Incremental Forming, Proceedings in Manufacturing Systems, Volume 9, Issue 2, 2014, ISSN 2067-9238, pp. 99-104,
DOI: https://doi.org/10.2478/aucts-2020-0008 | Journal eISSN: 2668-6449 | Journal ISSN: 1583-7149
Language: English
Page range: 49 - 56
Published on: Dec 31, 2020
Published by: Lucian Blaga University of Sibiu
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2020 Iosif Adrian Marosan, George Constantin, Anca Chicea, Alexandru Bârsan, published by Lucian Blaga University of Sibiu
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.