IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i12p1977-d980690.html
   My bibliography  Save this article

Bale Collection Path Planning Using an Autonomous Vehicle with Neighborhood Collection Capabilities

Author

Listed:
  • Saira Latif

    (Department of Engineering Sciences and Mathematics, Luleå University of Technology (LTU), SE-971 87 Luleå, Sweden)

  • Torbjörn Lindbäck

    (Department of Engineering Sciences and Mathematics, Luleå University of Technology (LTU), SE-971 87 Luleå, Sweden)

  • Magnus Karlberg

    (Department of Engineering Sciences and Mathematics, Luleå University of Technology (LTU), SE-971 87 Luleå, Sweden)

  • Johanna Wallsten

    (Department of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden)

Abstract

This research was mainly focused on the evaluation of path planning approaches as a prerequisite for the automation of bale collection operations. A comparison between a traditional bale collection path planning approach using traditional vehicles such as tractors, and loaders with an optimized path planning approach using a new autonomous articulated concept vehicle with neighborhood reach capabilities (AVN) was carried out. Furthermore, the effects of carrying capacity on reduction in the working distance of the bale collection operation was also studied. It was concluded that the optimized path planning approach using AVN with increased carrying capacity significantly reduced the working distance for the bale collection operation and can thus improve agricultural sustainability, particularly within forage handling.

Suggested Citation

  • Saira Latif & Torbjörn Lindbäck & Magnus Karlberg & Johanna Wallsten, 2022. "Bale Collection Path Planning Using an Autonomous Vehicle with Neighborhood Collection Capabilities," Agriculture, MDPI, vol. 12(12), pages 1-20, November.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:12:p:1977-:d:980690
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/12/1977/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/12/12/1977/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hailin Wu & Fengming Tao & Bo Yang, 2020. "Optimization of Vehicle Routing for Waste Collection and Transportation," IJERPH, MDPI, vol. 17(14), pages 1-26, July.
    2. Mikkel Sigurd & David Pisinger & Michael Sig, 2004. "Scheduling Transportation of Live Animals to Avoid the Spread of Diseases," Transportation Science, INFORMS, vol. 38(2), pages 197-209, May.
    3. Martin Filip & Tomas Zoubek & Roman Bumbalek & Pavel Cerny & Carlos E. Batista & Pavel Olsan & Petr Bartos & Pavel Kriz & Maohua Xiao & Antonin Dolan & Pavol Findura, 2020. "Advanced Computational Methods for Agriculture Machinery Movement Optimization with Applications in Sugarcane Production," Agriculture, MDPI, vol. 10(10), pages 1-20, September.
    4. J-F Cordeau & M Gendreau & G Laporte & J-Y Potvin & F Semet, 2002. "A guide to vehicle routing heuristics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(5), pages 512-522, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jin Yuan & Wei Ji & Qingchun Feng, 2023. "Robots and Autonomous Machines for Sustainable Agriculture Production," Agriculture, MDPI, vol. 13(7), pages 1-4, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Massimiliano Caramia & Francesca Guerriero, 2010. "A Milk Collection Problem with Incompatibility Constraints," Interfaces, INFORMS, vol. 40(2), pages 130-143, April.
    2. Wendolsky, Rolf & Scheuerer, Stephan, 2006. "A Cluster Based Scatter Search Heuristic for the Vehicle Routing Problem," University of Regensburg Working Papers in Business, Economics and Management Information Systems 415, University of Regensburg, Department of Economics.
    3. E A Silver, 2004. "An overview of heuristic solution methods," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(9), pages 936-956, September.
    4. Calvete, Herminia I. & Gale, Carmen & Oliveros, Maria-Jose & Sanchez-Valverde, Belen, 2007. "A goal programming approach to vehicle routing problems with soft time windows," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1720-1733, March.
    5. Vincent F. Yu & Panca Jodiawan & Shih-Wei Lin & Winy Fara Nadira & Anna Maria Sri Asih & Le Nguyen Hoang Vinh, 2024. "Using Simulated Annealing to Solve the Multi-Depot Waste Collection Vehicle Routing Problem with Time Window and Self-Delivery Option," Mathematics, MDPI, vol. 12(3), pages 1-20, February.
    6. Asif Iqbal & Abdullah Yasar & Abdul-Sattar Nizami & Rafia Haider & Faiza Sharif & Imran Ali Sultan & Amtul Bari Tabinda & Aman Anwer Kedwaii & Muhammad Murtaza Chaudhary, 2022. "Municipal Solid Waste Collection and Haulage Modeling Design for Lahore, Pakistan: Transition toward Sustainability and Circular Economy," Sustainability, MDPI, vol. 14(23), pages 1-39, December.
    7. Derigs, U. & Kaiser, R., 2007. "Applying the attribute based hill climber heuristic to the vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 177(2), pages 719-732, March.
    8. Fleming, Christopher L. & Griffis, Stanley E. & Bell, John E., 2013. "The effects of triangle inequality on the vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 224(1), pages 1-7.
    9. Felipe, Angel & Teresa Ortuño, M. & Tirado, Gregorio, 2011. "Using intermediate infeasible solutions to approach vehicle routing problems with precedence and loading constraints," European Journal of Operational Research, Elsevier, vol. 211(1), pages 66-75, May.
    10. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    11. Drexl, Michael & Schneider, Michael, 2015. "A survey of variants and extensions of the location-routing problem," European Journal of Operational Research, Elsevier, vol. 241(2), pages 283-308.
    12. Wanting Zhang & Ming Zeng & Peng Guo & Kun Wen, 2022. "Variable Neighborhood Search for Multi-Cycle Medical Waste Recycling Vehicle Routing Problem with Time Windows," IJERPH, MDPI, vol. 19(19), pages 1-25, October.
    13. Stefan Vonolfen & Michael Affenzeller, 2016. "Distribution of waiting time for dynamic pickup and delivery problems," Annals of Operations Research, Springer, vol. 236(2), pages 359-382, January.
    14. Angel Juan & Javier Faulin & Albert Ferrer & Helena Lourenço & Barry Barrios, 2013. "MIRHA: multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(1), pages 109-132, April.
    15. Ashlea Bennett Milburn & Emre Kirac & Mina Hadianniasar, 2017. "Case Article—Growing Pains: A Case Study for Large-Scale Vehicle Routing," INFORMS Transactions on Education, INFORMS, vol. 17(2), pages 75-80, January.
    16. Frey, Christian M.M. & Jungwirth, Alexander & Frey, Markus & Kolisch, Rainer, 2023. "The vehicle routing problem with time windows and flexible delivery locations," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1142-1159.
    17. J Berger & M Barkaoui, 2003. "A new hybrid genetic algorithm for the capacitated vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(12), pages 1254-1262, December.
    18. Jorge Oyola & Halvard Arntzen & David L. Woodruff, 2017. "The stochastic vehicle routing problem, a literature review, Part II: solution methods," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(4), pages 349-388, December.
    19. Adejuyigbe O. Fajemisin & Steven D. Prestwich & Laura Climent, 2023. "Cutting uncertain stock and vehicle routing in a sustainability forestry harvesting problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 139-164, April.
    20. Sun, Peng & Veelenturf, Lucas P. & Hewitt, Mike & Van Woensel, Tom, 2018. "The time-dependent pickup and delivery problem with time windows," Transportation Research Part B: Methodological, Elsevier, vol. 116(C), pages 1-24.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:12:y:2022:i:12:p:1977-:d:980690. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.