Development, Integration, and Field Experiment Optimization of an Autonomous Banana-Picking Robot

Tianci Chen, Shiang Zhang, Jiazheng Chen, Genping Fu, Yipeng Chen and Lixue Zhu ()
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Tianci Chen: College of Engineering, South China Agricultural University, Guangzhou 510642, China
Shiang Zhang: College of Innovation and Entrepreneurship, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China
Jiazheng Chen: College of Mechanical and Electrical Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China
Genping Fu: College of automation, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China
Yipeng Chen: College of Mechanical and Electrical Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China
Lixue Zhu: College of Mechanical and Electrical Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China

Agriculture, 2024, vol. 14, issue 8, 1-20

Abstract: The high growth height and substantial weight of bananas present challenges for robots to harvest autonomously. To address the issues of high labor costs and low efficiency in manual banana harvesting, a highly autonomous and integrated banana-picking robot is proposed to achieve autonomous harvesting of banana bunches. A prototype of the banana-picking robot was developed, featuring an integrated end-effector capable of clamping and cutting tasks on the banana stalks continuously. To enhance the rapid and accurate identification of banana stalks, a target detection vision system based on the YOLOv5s deep learning network was developed. Modules for detection, positioning, communication, and execution were integrated to successfully develop a banana-picking robot system, which has been tested and optimized in multiple banana plantations. Experimental results show that this robot can continuously harvest banana bunches. The average precision of detection is 99.23%, and the location accuracy is less than 6 mm. The robot picking success rate is 91.69%, and the average time from identification to harvesting completion is 33.28 s. These results lay the foundation for the future application of banana-picking robots.

Keywords: banana; picking robot; end-effector; stalk detection; harvesting optimization (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: 2024
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