Uploaded March 2026 | Updated September 2026, 3 weeks ago
Can physics and artificial intelligence help harvest the future of agriculture?
At the APS Global Physics Summit, we met Nursultan Khudayberdiev (Sam), a young researcher from California State University, Fresno, who is building a robotic arm designed to identify and gently pick strawberries using computer vision and machine learning.
Sam’s system uses AI image recognition (YOLOv8) to detect fruit and guide the robotic arm toward it with precision. The goal is to eventually mount the robot on a rover that can navigate fields and harvest strawberries in environments that may be difficult or unsafe for humans—such as extreme heat or around pesticides.
What makes the project especially interesting is how physics connects directly to the engineering. Sam uses ideas from electrodynamics and numerical relaxation methods to help the robot minimize positional error as it moves toward a target fruit, translating concepts from physics classrooms into practical robotics.
The current prototype works with apples while the AI model and precision systems are refined—because strawberries are much smaller and far more delicate. The ultimate goal is to create a system that can accurately detect and pick fragile fruit without damaging it.
Even better, Sam has made the entire project open-source, meaning researchers and developers anywhere can download the code, train it on new datasets, and adapt it to harvest different crops.
Inspired by Iron Man as a kid and now presenting his work at his first APS meeting, Sam represents the next generation of physicists applying scientific tools to real-world challenges—from agriculture to robotics and beyond.
Watch more stories from the APS Global Physics Summit on APS TV.
Can physics and artificial intelligence help harvest the future of agriculture?
At the APS Global Physics Summit, we met Nursultan Khudayberdiev (Sam), a young researcher from California State University, Fresno, who is building a robotic arm designed to identify and gently pick strawberries using computer vision and machine learning.
Sam’s system uses AI image recognition (YOLOv8) to detect fruit and guide the robotic arm toward it with precision. The goal is to eventually mount the robot on a rover that can navigate fields and harvest strawberries in environments that may be difficult or unsafe for humans—such as extreme heat or around pesticides.
What makes the project especially interesting is how physics connects directly to the engineering. Sam uses ideas from electrodynamics and numerical relaxation methods to help the robot minimize positional error as it moves toward a target fruit, translating concepts from physics classrooms into practical robotics.
The current prototype works with apples while the AI model and precision systems are refined—because strawberries are much smaller and far more delicate. The ultimate goal is to create a system that can accurately detect and pick fragile fruit without damaging it.
Even better, Sam has made the entire project open-source, meaning researchers and developers anywhere can download the code, train it on new datasets, and adapt it to harvest different crops.
Inspired by Iron Man as a kid and now presenting his work at his first APS meeting, Sam represents the next generation of physicists applying scientific tools to real-world challenges—from agriculture to robotics and beyond.
Watch more stories from the APS Global Physics Summit on APS TV.
