Development of an Autonomous Mobile Towing Vehicle for Logistic Tasks

  • Cláudia Rocha
  • Ivo Sousa
  • Francisco Ferreira
  • Héber Sobreira
  • José LimaEmail author
  • Germano Veiga
  • A. Paulo Moreira
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1092)


Frequently carrying high loads and performing repetitive tasks compromises the ergonomics of individuals, a recurrent scenario in hospital environments. In this paper, we design a logistic planner of a fleet of autonomous mobile robots for the automation of transporting trolleys around the hospital, which is independent of the space configuration, and robust to loss of network and deadlocks. Our robotic solution has an innovative gripping system capable of grasping and pulling non-modified standard trolleys just by coupling a plate. Robots are able to navigate autonomously, to avoid obstacles assuring the safety of operators, to identify and dock a trolley, to access charging stations and elevators, and to communicate with the latter. An interface was built allowing users to command the robots through a web server. It is shown how the proposed methodology behaves in experiments conducted at the Faculty of Engineering of the University of Porto and Braga’s Hospital.


Mobile robot Autonomous driving Trolley docking Ergonomics 



This work is financed by the ERDF – European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme, and by National Funds through the Portuguese funding agency, FCT-Fundação para a Ciência e a Tecnologia, within project SAICTPAC/0034/2015- POCI-01- 0145-FEDER-016418.

Authors would like to acknowledge to Trivalor, Itau and Gertal for the support of the project RDH.


  1. 1.
    Center for Disease Control and Prevention: Work-related musculoskeletal disorders and ergonomics (2018).
  2. 2.
    EvoCart: Evocart - advanced motion technology (2019).
  3. 3.
    Ferreira, F., Sobreira, H., Veiga, G., Moreira, A.: Landmark detection for docking tasks, pp. 3–13 (2018)Google Scholar
  4. 4.
    Gouveia, M., Moreira, A., Costa, P., Reis, L., Ferreira, M.: Robustness and precision analysis in map-matching based mobile robot self-localization (2009)Google Scholar
  5. 5.
    Iowa State University Department Environment Health and Safety: Ergonomics (2016).
  6. 6.
    Kochan, A.: BMW uses even more robots for both flexibility and quality. J. Ind. Robots (2005).
  7. 7.
    Krishnamurthy, B., Evans, J.: HelpMate: a robotic courier for hospital use. In: IEEE International Conference on Systems, Man, and Cybernetics (1992)Google Scholar
  8. 8.
    Lauer, M., Lange, S., Riedmiller, M.: Calculating the perfect match: an efficient and accurate approach for robot self-localization. In: Bredenfeld, A., Jacoff, A., Noda, I., Takahashi, Y. (eds.) RoboCup 2005: Robot Soccer World Cup IX, pp. 142–153. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  9. 9.
    Martinez, A., Fernández, E.: Learning ROS for Robotics Programming. Packt Publishing, Birmingham (2013)Google Scholar
  10. 10.
    Messia, J., Ventura, R., Lima, P., Sequeira, J., Alvito, P., Marques, C., Carriço, P.: A robotic platform for edutainment activities in a pediatric hospital. In: 2014 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) (2014)Google Scholar
  11. 11.
    MiR: Mobile industrial robots (2019).
  12. 12.
    Santos, J., Costa, P., Rocha, L., Moreira, A., Veiga, G.: Time enhanced A*: towards to the development of a new approach for multi-robot coordination. In: IEEE International Conference on Industrial Technology (ICIT) (2015)Google Scholar
  13. 13.
    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.P., Moreira, A.P., Lima, P.U., Montano, L., Muñoz-Martinez, V. (eds.) Robot 2015: Second Iberian Robotics Conference, pp. 81–92. Springer, Cham (2016)CrossRefGoogle Scholar
  14. 14.
    Savant Automation: Savant automation - AGV systems (2019).
  15. 15.
    Skapinyecz, R., Illés, B., Bányai, A.: Logistic aspects of industry 4.0. In: IOP Conference Series: Materials Science and Engineering, vol. 448, no. 1 (2018)Google Scholar
  16. 16.
    Sobreira, H., Rocha, L., Costa, C., Lima, J., Costa, P., Moreira, A.P.: 2D cloud template matching-a comparison between iterative closest point and perfect match. In: 2016 International Conference on Autonomous Robot Systems and Competitions (ICARSC), pp. 53–59 (2016)Google Scholar
  17. 17.
    Sobreira, H., Costa, C.M., Sousa, I., Rocha, L., Lima, J., Farias, P.C.M.A., Costa, P., Moreira, A.P.: Map-matching algorithms for robot self-localization: a comparison between perfect match, iterative closest point and normal distributions transform. J. Intell. Robot. Syst. (2018).
  18. 18.
    Sobreira, H., Moreira, A., Costa, P., Lima, J.: Robust mobile robot localization based on a security laser: an industry case study. Ind. Robot: Int. J. 43, 596–606 (2016)CrossRefGoogle Scholar
  19. 19.
    Sobreira, H., Pinto, M., Moreira, A.P., Costa, P.G., Lima, J.: Robust robot localization based on the perfect match algorithm. In: Moreira, A.P., Matos, A., Veiga, G. (eds.) CONTROLO’2014 – Proceedings of the 11th Portuguese Conference on Automatic Control, pp. 607–616. Springer, Cham (2015)Google Scholar
  20. 20.
    Swisslog: Swisslog - healthcare and logistics automation (2019).

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Cláudia Rocha
    • 1
  • Ivo Sousa
    • 1
  • Francisco Ferreira
    • 1
  • Héber Sobreira
    • 1
  • José Lima
    • 1
    • 2
    Email author
  • Germano Veiga
    • 1
    • 3
  • A. Paulo Moreira
    • 1
    • 3
  1. 1.INESC TEC - INESC Technology and SciencePortoPortugal
  2. 2.CeDRI - Research Centre in Digitalization and Intelligent Robotics, Polytechnic Institute of BragançaBragançaPortugal
  3. 3.Faculty of Engineering of University of PortoPortoPortugal

Personalised recommendations