Abstract
Automated guided vehicles (AGV) represent a key element in industries’ intralogistics and the use of AGV fleets bring multiple advantages. Nevertheless, coordinating a fleet of AGV is already a complex task but when exposed to delays in the trajectory and communication faults it can represent a threat, compromising the safety, productivity and efficiency of these systems. Concerning this matter, trajectory planning algorithms allied with supervisory systems have been studied and developed. This article aims to, based on work developed previously, implement and test a Multi AGV Supervisory System on real robots and analyse how the system responds to the dynamic of a real environment, analysing its intervention, what influences it and how the execution time is affected.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Automated Guided Vehicle Market Size, Share & Trends Analysis Report By Vehicle Type, by Navigation Technology, by Application, by End-use Industry, by Component, by Battery Type, by Region, and Segment Forecasts, https://www.grandviewresearch.com/industry-analysis/automated-guided-vehicle-agv-market. Accessed 21 Jan 2021
The Advantages and Disadvantages of Automated Guided Vehicles (AGVs). https://www.conveyco.com/advantages-disadvantages-automated-guided-vehicles-agvs. Accessed 21 Jan 2021
Benefits of Industrial AGVs in Manufacturing. https://blog.pepperl-fuchs.us/4-benefits-of-industrial-agvs-in-manufacturing. Accessed 21 Jan 2021
Bittel, O., Blaich, M.: Mobile robot localization using beacons and the Kalman filter technique for the Eurobot competition. In: Obdržálek, D., Gottscheber, A. (eds.) EUROBOT 2011. CCIS, vol. 161, pp. 55–67. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21975-7_6
Cao, Y.U., Fukunaga, A.S., Kahng, A.: Cooperative mobile robotics: antecedents and directions. Autonom. Robot. 4, 7–24 (1997)
Garrido-Jurado, S., Muñoz Salinas, R., Madrid-Cuevas, F.J., Medina-Carnicer, R.: Generation of fiducial marker dictionaries using mixed integer linear programming. Patt. Recogn. 51, 481–491 (2016)
Gomes da Costa, P. L.: Planeamento Cooperativo de Tarefas e Trajectóriasem Múltiplos Robôs. PhD thesis, Faculdade de Engenharia da Universidade do Porto (2011)
Matos, D., Costa, P., Lima, J., Costa, P.: Multi AGV coordination tolerant to communication failures. Robotics 10(2), 55 (2021)
Romero-Ramirez, F.J., Muñoz-Salinas, R., Medina-Carnicer, R.: Speeded up detection of squared fiducial markers. Image Vis. Comput. 76, 38–47 (2018)
Santos, J., Costa, P., Rocha, L. F., Moreira, A. P., Veiga, G.: Time Enhanced A*: Towards the Development of a New Approach for Multi-Robot Coordination. In: Proceedings of the IEEE International Conference on Industrial Technology, pp. 3314–3319. Springer, Heidelberg (2015)
Santos J., Costa P., Rocha L., Vivaldini K., Moreira A.P., Veiga G.: Validation of a time based routing algorithm using a realistic automatic warehouse scenario. In: Reis, L., Moreira, A., Lima, P., Montano, L., Muñoz-Martinez, V. (eds.) ROBOT 2015: Second Liberian Robotics Conference: Advances in Robotics, vol. 2, pp. 81–92 (2016)
UDP (User Datagram Protocol). https://searchnetworking.techtarget.com. Accessed 13 June 2021
Ullrich, G.: The history of automated guided vehicle systems. In: Automated Guided Vehicle Systems, pp. 1–14. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-44814-4_1
Acknowledgements
This work is financed by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia within project UIDB/50014/2020.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Cruz, A., Matos, D., Lima, J., Costa, P., Costa, P. (2021). Multi AGV Industrial Supervisory System. In: Pereira, A.I., et al. Optimization, Learning Algorithms and Applications. OL2A 2021. Communications in Computer and Information Science, vol 1488. Springer, Cham. https://doi.org/10.1007/978-3-030-91885-9_15
Download citation
DOI: https://doi.org/10.1007/978-3-030-91885-9_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-91884-2
Online ISBN: 978-3-030-91885-9
eBook Packages: Computer ScienceComputer Science (R0)