Agronomy (Dec 2022)

Research on a Map-Based Cooperative Navigation System for Spraying–Dosing Robot Group

  • Jifeng Qin,
  • Wang Wang,
  • Wenju Mao,
  • Minxin Yuan,
  • Heng Liu,
  • Zhigang Ren,
  • Shuaiqi Shi,
  • Fuzeng Yang

DOI
https://doi.org/10.3390/agronomy12123114
Journal volume & issue
Vol. 12, no. 12
p. 3114

Abstract

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To solve the problem encountered when the spraying robot has run out of medicine even though the spraying task on the field is not complete, we developed a spraying–dosing robot group and proposed a collaborative navigation system based on an orchard map. Firstly, we constructed a 3D orchard point cloud map and set up navigation path points on the projected map. Secondly, we developed a master–slave command-based cooperative navigation strategy, where the spraying robot was the master and the dosing robot was the slave. Finally, the spraying robot and the dosing robot completed the cooperative navigation on the constructed map by using the pure pursuit algorithm and D-A control algorithm, respectively. To validate the cooperative navigation system, we conducted field tests on the separate communication and navigation control. The results of communication experiments demonstrated that the packet loss rate was less than 5%, which satisfied communication requirements. The experimental results of the navigation control demonstrated that the maximum value of the absolute lateral error is 24.9 cm for the spraying robot and 29.7 cm for the dosing robot. The collaborative navigation system proposed in this research can meet the automatic navigation requirements of the spraying–dosing robot group for collaborative tasks in traditional orchards.

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