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. 2022 Aug 1:13:960686.
doi: 10.3389/fpls.2022.960686. eCollection 2022.

Design and development of orchard autonomous navigation spray system

Shubo Wang  1 , Jianli Song  1 , Peng Qi  1 , Changjian Yuan  1 , Hecheng Wu  1 , Lanting Zhang  1 , Weihong Liu  1 , Yajia Liu  1 , Xiongkui He  1
Affiliations

Design and development of orchard autonomous navigation spray system

Shubo Wang et al. Front Plant Sci. .

Abstract

Driven by the demand for efficient plant protection in orchards, the autonomous navigation system for orchards is hereby designed and developed in this study. According to the three modules of unmanned system "perception-decision-control," the environment perception and map construction strategy based on 3D lidar is constructed for the complex environment in orchards. At the same time, millimeter-wave radar is further selected for multi-source information fusion for the perception of obstacles. The extraction of orchard navigation lines is achieved by formulating a four-step extraction strategy according to the obtained lidar data. Finally, aiming at the control problem of plant protection machine, the ADRC control strategy is adopted to enhance the noise immunity of the system. Different working conditions are designed in the experimental section for testing the obstacle avoidance performance and navigation accuracy of the autonomous navigation sprayer. The experimental results show that the unmanned vehicle can identify the obstacle quickly and make an emergency stop and find a rather narrow feasible area when a moving person or a different thin column is used as an obstacle. Many experiments have shown a safe distance for obstacle avoidance about 0.5 m, which meets the obstacle avoidance requirements. In the navigation accuracy experiment, the average navigation error in both experiments is within 15 cm, satisfying the requirements for orchard spray operation. A set of spray test experiments are designed in the final experimental part to further verify the feasibility of the system developed by the institute, and the coverage rate of the leaves of the canopy is about 50%.

Keywords: autonomous navigation; crawler sprayer; laser lidar; obstacle avoidance; orchard plant protection.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Overview of orchard environment.
FIGURE 2
FIGURE 2
Hardware module of orchard autonomous navigation spray system.
FIGURE 3
FIGURE 3
The main hardware distribution of the orchard autonomous navigation spray system.
FIGURE 4
FIGURE 4
Structure diagram of crawler chassis diagram.
FIGURE 5
FIGURE 5
Sensor and information processing module information transmission process.
FIGURE 6
FIGURE 6
Sprinkler distribution map.
FIGURE 7
FIGURE 7
Software block diagram of unmanned spray truck based on “perception decision control”. (A) Relationship between three layers. (B) Obstacle avoidance fusion output based on decision-level fusion.
FIGURE 8
FIGURE 8
Construction of local map based on RS-LiDAR-16. (A) Local map acquisition. (B) Schematic diagram of navigation line.
FIGURE 9
FIGURE 9
Navigation line extraction rules among fruit trees.
FIGURE 10
FIGURE 10
Definition of crawler coordinate system.
FIGURE 11
FIGURE 11
System control block diagram based on ADRC (ESO, extended state observer; TD, tracking differentiator; NLSEF, non-linear state error feedback).
FIGURE 12
FIGURE 12
Experimental flow chart.
FIGURE 13
FIGURE 13
Experiment of fixed human obstacle.
FIGURE 14
FIGURE 14
Experiment of fixed pole obstacle (Group 1).
FIGURE 15
FIGURE 15
Experiment of fixed pole obstacle (Group 2).
FIGURE 16
FIGURE 16
Experiment of moving person obstacle.
FIGURE 17
FIGURE 17
Experiment of moving pole obstacle.
FIGURE 18
FIGURE 18
Navigation accuracy test scheme.
FIGURE 19
FIGURE 19
Navigation accuracy experiment (Group 1).
FIGURE 20
FIGURE 20
Navigation accuracy experiment (Group 2).
FIGURE 21
FIGURE 21
Spray diagram and collection point layout.
See this image and copyright information in PMC

References

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