Optimal Path Generation with Obstacle Avoidance and Subfield Connection for an Autonomous Tractor

Tyler Parsons, Fattah Hanafi Sheikhha, Omid Ahmadi Khiyavi, Jaho Seo (), Wongun Kim and Sangdae Lee
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Tyler Parsons: Department of Automotive and Mechatronics Engineering, Ontario Tech University, Oshawa ON L1G 0C5, Canada
Fattah Hanafi Sheikhha: Department of Automotive and Mechatronics Engineering, Ontario Tech University, Oshawa ON L1G 0C5, Canada
Omid Ahmadi Khiyavi: Department of Automotive and Mechatronics Engineering, Ontario Tech University, Oshawa ON L1G 0C5, Canada
Jaho Seo: Department of Automotive and Mechatronics Engineering, Ontario Tech University, Oshawa ON L1G 0C5, Canada
Wongun Kim: Convergence Agricultural Machinery Group, Korea Institute of Industrial Technology, Gimje-si 54325, Jeollabuk-do, Republic of Korea
Sangdae Lee: Convergence Agricultural Machinery Group, Korea Institute of Industrial Technology, Gimje-si 54325, Jeollabuk-do, Republic of Korea

Agriculture, 2022, vol. 13, issue 1, 1-16

Abstract: As autonomous tractors become more common crop harvesting applications, the need to optimize the global servicing path becomes crucial for maximizing efficiency and crop yield. In recent years, several methods of path generation have been researched, but very few have studied their applications on complex field shapes. In this study, a method of creating the optimal servicing path for simple and complex field shapes is proposed. The proposed algorithm creates subfields for a target land, optimizes the track direction for several subfields individually, merges subfields that result in overall increased efficiency, and finds the minimum non-operating paths to travel from subfield to subfield while selecting the respective optimal subfield starting locations. Additionally, it is required that this process must be done within 3 seconds to meet performance requirements. Results from 3 separate field shapes show that the field traversal efficiency can range from 68.0% to 94.4%, and the coverage ratio can range from 98.8% to 99.9% for several different conditions. In comparison with previous studies using the same field shape, the proposed methods demonstrate an increase of 5.5% in field traversal efficiency.

Keywords: tractor; route optimization; direction angle optimization; field coverage ratio; subfield traversal order; obstacle avoidance; global path generation (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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