image: A farm robot using lidar shows it can harvest strawberries from a high-bed cultivation field.
Credit: Osaka Metropolitan University
Strawberry fields forever will exist for the in-demand fruit, but the laborers who do the backbreaking work of harvesting them might continue to dwindle. While raised, high-bed cultivation somewhat eases the manual labor, the need for robots to help harvest strawberries, tomatoes, and other such produce is apparent.
As a first step, Osaka Metropolitan University Assistant Professor Takuya Fujinaga has developed an algorithm for robots to autonomously drive in two modes: moving to a pre-designated destination and moving alongside raised cultivation beds. The Graduate School of Engineering researcher experimented with an agricultural robot that utilizes lidar point cloud data to map the environment.
Lidar, available on some high-end, pro-level smartphones and used by autonomous vehicles, uses light in laser pulses as a remote sensing method. The farming robot can thus move accurately while maintaining a constant distance from the cultivation bed, with its effectiveness verified in virtual and actual environments.
“If robots can move around the farm more precisely, the range of tasks that they can perform automatically will expand, not only for harvesting, but also for monitoring for disease and pruning,” Professor Fujinaga explained. “My research shows a possibility, and once this type of agricultural robot becomes more practical to use, it will make a significant contribution to improving work efficiency and reducing labor, especially for high-bed cultivation.”
The findings were published in Computers and Electronics in Agriculture.
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Journal
Computers and Electronics in Agriculture
Method of Research
Experimental study
Subject of Research
Not applicable
Article Title
Autonomous navigation method for agricultural robots in high-bed cultivation environments
Article Publication Date
13-Feb-2025
COI Statement
The author declares that I have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.