Skip to main content
SpringerLink
Log in

Ocean Relief-Based Heuristic for Robotic Mapping

  • Conference paper
  • First Online:
Robot 2023: Sixth Iberian Robotics Conference (ROBOT 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 978))

Included in the following conference series:

  • 19 Accesses

Abstract

Order picking has driven an increase in the number of logistics researchers. Robotics can help reduce the operational cost of such a process, eliminating the need for a human operator to perform trivial and dangerous tasks such as moving around the warehouse. However, for a mobile robot to perform such tasks, certain problems, such as defining the best path, must be solved. Among the most prominent techniques applied in the calculation of the trajectories of these robotic agents are potential fields and the A* algorithm. However, these techniques have limitations. This study aims to demonstrate a new approach based on the behavior of oceanic relief to map an environment that simulates a logistics warehouse, considering distance, safety, and efficiency in trajectory planning. In this manner, we seek to solve some of the limitations of traditional algorithms. We propose a new mapping technique for mobile robots, followed by a new trajectory planning approach.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Arkin, R.C., Arkin, R.C., et al.: Behavior-based robotics. MIT press (1998)

    Google Scholar 

  2. Chiang, H.T., Malone, N., Lesser, K., Oishi, M., Tapia, L.: Path-guided artificial potential fields with stochastic reachable sets for motion planning in highly dynamic environments. In: 2015 IEEE International Conference on Robotics and Automation (ICRA), pp. 2347–2354. IEEE (2015)

    Google Scholar 

  3. Duchon, F., et al.: Path planning with modified a star algorithm for a mobile robot. Proc. Eng. 96, 59–69 (2014)

    Google Scholar 

  4. GKToday: Ocean relief : Key features and types of ocean relief (2016). https://www.gktoday.in/ocean-relief-key-features-and-types-of-ocean-relief/ (Accessed 02 Feb 2023)

  5. Guerra, M., Efimov, D., Zheng, G., Perruquetti, W.: Avoiding local minima in the potential field method using input-to-state stability. Control. Eng. Pract. 55, 174–184 (2016)

    Article  Google Scholar 

  6. Hart, P.E., Nilsson, N.J., Raphael, B.: A formal basis for the heuristic determination of minimum cost paths. IEEE Trans. Syst. Sci. Cybernet. 4(2), 100–107 (1968)

    Article  Google Scholar 

  7. Khatib, O.: Real-time obstacle avoidance for manipulators and mobile robots. In IEEE International Conference on Robotics and Automation (1985)

    Google Scholar 

  8. LaValle, S.M.: Planning algorithms. Cambridge university press (2006)

    Google Scholar 

  9. Martis, W.P., Rao, S.: Cooperative collision avoidance in mobile robots using dynamic vortex potential fields. In: 2023 9th International Conference on Automation, Robotics and Applications (ICARA), pp. 60–64. IEEE (2023)

    Google Scholar 

  10. Parker, L.E.: Path planning and motion coordination in multiple mobile robot teams. Encyclopedia Complex. Syst. Sci., 5783–5800 (2009)

    Google Scholar 

  11. Rasekhipour, Y., Khajepour, A., Chen, S.K., Litkouhi, B.: A potential field-based model predictive path-planning controller for autonomous road vehicles. IEEE Trans. Intell. Transp. Syst. 18(5), 1255–1267 (2016)

    Article  Google Scholar 

  12. Rohmer, E., Singh, S.P., Freese, M.: V-rep: a versatile and scalable robot simulation framework. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1321–1326. IEEE (2013)

    Google Scholar 

  13. Sabudin, E., Omar, R., Che Ku Melor, C.: Potential field methods and their inherent approaches for path planning. ARPN J. Eng. Appli. Sci. 11(18), 10801–10805 (2016)

    Google Scholar 

  14. Shiau, J.Y., Liao, T.C.: Developing an order picking policy for economical packing. In: Proceedings of 2013 IEEE International Conference on Service Operations and Logistics, and Informatics, pp. 387–392. IEEE (2013)

    Google Scholar 

  15. Tessler, M.G., Mahiques, M.M.d.: Processos oceânicos e a fisiografia dos fundos marinhos. Oficina de textos (2000)

    Google Scholar 

  16. Vlantis, P., Bechlioulis, C.P., Kyriakopoulos, K.J.: Robot navigation in complex workspaces employing harmonic maps and adaptive artificial potential fields. Sensors 23(9), 4464 (2023)

    Article  Google Scholar 

  17. Wang, Q., Mcintosh, R., Brain, M.: A new-generation automated warehousing capability. Int. J. Comput. Integr. Manuf. 23(6), 565–573 (2010)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Graduate School of Electrical Engineering and Computer Science (CPGEI), Universidade Tecnológica Federal do Paraná (UTFPR), Curitiba, Brazil

    Filipe Testa Daros, Marco Antônio Simões Teixeira, Ronnier Frates Rohrich & André Schneider de Oliveira

  2. Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Politécnico de Bragança, Campus de Santa Apolonia, Braganca, Portugal

    Jose Lima

  3. INESC Technology and Science, Porto, Portugal

    Jose Lima

Authors
  1. Filipe Testa Daros
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marco Antônio Simões Teixeira
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ronnier Frates Rohrich
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jose Lima
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. André Schneider de Oliveira
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Filipe Testa Daros .

Editor information

Editors and Affiliations

  1. Dep. de Eng. Electrotecnica e de Computadores, University of Coimbra, Coimbra, Portugal

    Lino Marques

  2. Department of Electrónica Industrial, University of Minho, Escola de Engenharia, Guimarães, Portugal

    Cristina Santos

  3. Department of Electrical Engineering, ESTIG, Polytechnic Institute of Bragança, Bragança, Portugal

    José Luís Lima

  4. Centro Universitario de la Defensa, Zaragoza, Spain

    Danilo Tardioli

  5. Centre for Automation and Robotics UPM-CSIC, Universidad Politécnica de Madrid, Madrid, Spain

    Manuel Ferre

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Daros, F.T., Teixeira, M.A.S., Rohrich, R.F., Lima, J., de Oliveira, A.S. (2024). Ocean Relief-Based Heuristic for Robotic Mapping. In: Marques, L., Santos, C., Lima, J.L., Tardioli, D., Ferre, M. (eds) Robot 2023: Sixth Iberian Robotics Conference. ROBOT 2023. Lecture Notes in Networks and Systems, vol 978. Springer, Cham. https://doi.org/10.1007/978-3-031-59167-9_12

Download citation

Publish with us

Policies and ethics

Search

Navigation