Design, Integration, and Experiment of a Multi-Variety Rice Seedling Transplanting Robot with a Force–Position-Controlled Rigid–Flexible Coupled End Effector

To address the high labor intensity, low efficiency, and unstable precision of manual transplanting in rice breeding experimental fields—where conventional transplanters fail to meet the operational requirements—an intelligent transplanting robot for multi-variety rice seedlings was designed. Based on an analysis of the agronomic parameters of rice seedling transplanting, an integrated system architecture consisting of a tracked mobile chassis, a six-degree-of-freedom collaborative robotic arm, and a custom-designed end effector was constructed. A bionic rigid–flexible coupled end effector was developed, and a force–position closed-loop control strategy was established. The YOLOv5s algorithm combined with distinct-color auxiliary markers was adopted to achieve rapid recognition of multi-variety rice seedlings, and hand–eye calibration was used to realize pose transformation. Forward and inverse kinematics analyses were conducted to verify the reachability of the workspace. Finally, a multi-variety rice seedling transplanting test bench was built to validate the robot’s performance. The results showed that the rice seedling transplanting success rate reached 94.90%, the transplanting accuracy rate reached 97.96%, the average damage rate was only 3.06%, and the transplanting time was 7.85 s per hill. All metrics satisfied the requirements of breeding trials for operational accuracy and data consistency.

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Publication Details

Journal
Agriculture
Published
2026-11-02
DOI
https://doi.org/10.3390/agriculture16212390
Primary Topic
Smart Agriculture and AI
Type
article
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article

Design, Integration, and Experiment of a Multi-Variety Rice Seedling Transplanting Robot with a Force–Position-Controlled Rigid–Flexible Coupled End Effector

Chao Kong, Yaoyun Wu, Di Yu, Runxin Zhang et al.
Agriculture
Smart Agriculture and AI
article

Design, Integration, and Experiment of a Multi-Variety Rice Seedling Transplanting Robot with a Force–Position-Controlled Rigid–Flexible Coupled End Effector

Chao Kong, Yaoyun Wu, Di Yu, Runxin Zhang, Qingyu Zhang, Zhenxing Su
article en

Abstract

To address the high labor intensity, low efficiency, and unstable precision of manual transplanting in rice breeding experimental fields—where conventional transplanters fail to meet the operational requirements—an intelligent transplanting robot for multi-variety rice seedlings was designed. Based on an analysis of the agronomic parameters of rice seedling transplanting, an integrated system architecture consisting of a tracked mobile chassis, a six-degree-of-freedom collaborative robotic arm, and a custom-designed end effector was constructed. A bionic rigid–flexible coupled end effector was developed, and a force–position closed-loop control strategy was established. The YOLOv5s algorithm combined with distinct-color auxiliary markers was adopted to achieve rapid recognition of multi-variety rice seedlings, and hand–eye calibration was used to realize pose transformation. Forward and inverse kinematics analyses were conducted to verify the reachability of the workspace. Finally, a multi-variety rice seedling transplanting test bench was built to validate the robot’s performance. The results showed that the rice seedling transplanting success rate reached 94.90%, the transplanting accuracy rate reached 97.96%, the average damage rate was only 3.06%, and the transplanting time was 7.85 s per hill. All metrics satisfied the requirements of breeding trials for operational accuracy and data consistency.

AgricultureVol. 16(21)
Northeast Forestry University (CN)
Openalex Percentile: Top 17%
Smart Agriculture and AI
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