AI-powered robot learns how to harvest tomatoes more efficiently

Science News from research organizations AI-powered robot learns how to harvest tomatoes more efficiently This tomato-picking robot doesn’t just see fruit—it figures out the smartest way to grab it. Date: March 18, 2026 Source: Osaka Metropolitan University Summary: A new tomato-picking robot...

Science News from research organizations AI-powered robot learns how to harvest tomatoes more efficiently This tomato-picking robot doesn’t just see fruit—it figures out the smartest way to grab it. Date: March 18, 2026 Source: Osaka Metropolitan University Summary: A new tomato-picking robot is learning to think before it acts. Instead of simply identifying ripe fruit, it predicts how easy each tomato will be to harvest and adjusts its approach accordingly. This smarter strategy boosted success rates to 81%, with the robot even switching angles when needed. The breakthrough could pave the way for farms where robots and humans work side by side. Share: Facebook Twitter Pinterest LinkedIN Email FULL STORY Scientists have created a robot that decides how easy a tomato is to pick before trying—dramatically improving its success. By adapting its approach on the fly, it marks a big step toward intelligent, collaborative farming. Credit: Shutterstock Farm labor shortages are pushing agriculture toward greater automation, especially when it comes to harvesting. But not all crops are easy for machines to handle. Tomatoes, for example, grow in clusters, which means a robot must carefully select ripe fruit while leaving unripe ones untouched. This requires precise control and smart decision-making. To tackle this challenge, Assistant Professor Takuya Fujinaga of Osaka Metropolitan University's Graduate School of Engineering developed a system that trains robots to assess how easy each tomato is to harvest before attempting to pick it. His approach combines image recognition with statistical analysis to determine the best angle for picking each fruit. The robot analyzes visual details such as the tomato itself, its stems, and whether it is hidden behind leaves or other parts of the plant. These inputs guide the robot in choosing the most effective way to approach and pick the fruit. From Detection to "Harvest-Ease" Decision-Making This method shifts away from traditional systems that focus only on detecting and identifying fruit. Instead, Fujinaga introduces what he calls "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. In testing, the system achieved an 81% success rate, exceeding expectations. About one-quarter of the successful picks came from tomatoes that were harvested from the side after an initial front-facing attempt failed. This indicates the robot can adjust its approach when the first attempt is not successful. The research underscores how many variables affect robotic harvesting, including how tomatoes cluster, the shape and position of stems, surrounding leaves, and visual obstruction. "This research establishes 'ease of harvesting' as a quantitatively evaluable metric, bringing us one step closer to the realization of agricultural robots that can make informed decisions and act intelligently," Fujinaga said. Future of Human-Robot Collaboration in Farming Looking ahead, Fujinaga envisions robots that can independently judge when crops are ready to be picked. "This is expected to usher in a new form of agriculture where robots and humans collaborate," he explained. "Robots will automatically harvest tomatoes that are easy to pick, while humans will handle the more challenging fruits." The findings were published in Smart Agricultural Technology. RELATED TOPICS Computers & Math Robotics Statistics Artificial Intelligence Communications Mathematics Computational Biology Information Technology Mathematical Modeling RELATED TERMS Robot Industrial robot Robot calibration Humanoid robot Gross domestic product Robotic surgery Trigonometry Artificial intelligence Story Source: Materials provided by Osaka Metropolitan University. Note: Content may be edited for style and length. Journal Reference: Takuya Fujinaga. Realizing an intelligent agricultural robot: An analysis of the ease of tomato harvesting. Smart Agricultural Technology, 2025; 12: 101538 DOI: 10.1016/j.atech.2025.101538 Cite This Page: MLA APA Chicago Osaka Metropolitan University. "AI-powered robot learns how to harvest tomatoes more efficiently." ScienceDaily. ScienceDaily, 18 March 2026. . Osaka Metropolitan University. (2026, March 18). AI-powered robot learns how to harvest tomatoes more efficiently. ScienceDaily. Retrieved July 13, 2026 from www.sciencedaily.com/releases/2026/03/260317064512.htm Osaka Metropolitan University. "AI-powered robot learns how to harvest tomatoes more efficiently." ScienceDaily. www.sciencedaily.com/releases/2026/03/260317064512.htm (accessed July 13, 2026). Explore More from ScienceDaily RELATED STORIES Exposure to Soft Robots Decreases Human Fears About Working With Them Dec. 5, 2023 — Seeing robots made with soft, flexible parts in action appears to lower people's anxiety about working with them or even being replaced by them. A study found that watching videos of a soft ... Research in Japan Shows the Way Toward Tactile and Proximity Sensing in Large Soft Robots Apr. 12, 2023 — To make human-robot interactions safer and more fruitful, robots should be capable of sensing their environment. In a recent study, researchers developed a novel robotic link with tactile and ... 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Source: ScienceDaily AI — Published March 18, 2026 at 04:26 UTC — Category: Research