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

Saira Latif (), Torbjörn Lindbäck, Magnus Karlberg and Johanna Wallsten
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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

Agriculture, 2022, vol. 12, issue 12, 1-20

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.

Keywords: agriculture; path planning; neighborhood collection; autonomous vehicle; genetic algorithm; global optimization; bale collection problem; forage handling (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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