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A Pesticide Spraying Mission Allocation and Path Planning with Multicopters

  • Jing Huang
  • , Baihui Du
  • , Youmin Zhang*
  • , Quan Quan
  • , Ban Wang*
  • , Lingxia Mu
  • *Corresponding author for this work
  • Xi'an University of Technology
  • Jiujiang Measuring Test Technology Research Institute
  • China Electronics Corporation
  • Concordia University
  • Northwestern Polytechnical University Xian

Research output: Contribution to journalArticlepeer-review

Abstract

This article presents a mission allocation and path-planning solution for the pesticide spraying mission of dense trees in hilly terrains using cooperative multicopters. The problem is formulated as a single-depot single-end multiple traveling salesman problem (mTSP). Three different algorithms, namely classical mTSP algorithm, Grouping-TSP combined algorithm, and Grouping-TSP decoupled algorithm, are developed to solve the proposed mTSP. Simulation results indicate that the classical mTSP algorithm provides an evenly distributed task allocation while the Grouping-TSP combined algorithm delivers the optimal solution. In addition, the Grouping-TSP decoupled algorithm minimizes computational complexity. Both Grouping-TSP algorithms integrate a subregions segmentation process to guarantee collision avoidance between the multicopters.

Original languageEnglish
Pages (from-to)2277-2291
Number of pages15
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume60
Issue number2
DOIs
StatePublished - 1 Apr 2024

Keywords

  • Mission assignment
  • multicopters
  • multiple traveling salesman problem (mTSP)
  • path planning
  • point cloud
  • precision spraying

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