RoboCrop: Teaching Robots How To Pick Tomatoes

alternative_right quotes a report from Phys.org: To teach robots how to become tomato pickers, Osaka Metropolitan University Assistant Professor Takuya Fujinaga, Graduate School of Engineering, programmed them to evaluate the ease of harvesting for each tomato before attempting to pick it. Fujinaga's new model uses image recognition paired with statistical analysis to evaluate the optimal approach direction for each fruit. The system involves image processing/vision of the fruit, its stems, and whether it is concealed behind another part of the plant. These factors inform robot control decisions and help it choose the best approach.

The model represents a shift in focus from the traditional 'detection/recognition' model to what Fujinaga calls a 'harvest-ease estimation.' 'This moves beyond simply asking 'can a robot pick a tomato?' to thinking about 'how likely is a successful pick?', which is more meaningful for real-world farming,' he explained. When tested, Fujinaga's new model demonstrated an 81% success rate, far above predictions. Notably, about a quarter of the successes were tomatoes that were successfully harvested from the right or left side that had previously failed to be harvested by a front approach. This suggested that the robot changed its approach direction when it initially struggled to pick the fruit. 'This is expected to usher in a new form of agriculture where robots and humans collaborate,' said Fujinaga. 'Robots will automatically harvest tomatoes that are easy to pick, while humans will handle the more challenging fruits.'

The findings are published in Smart Agricultural Technology.

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