Cambridge scientists develop vegebot that uses artificial intelligence (AI) to identify and harvest commonplace but challenging agricultural crops.
Machine learning is an application of (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
It has now been successfully tested in a variety of field conditions in cooperation a local fruit and vegetable co-operative, according to the study.
Although the prototype is nowhere near as fast or efficient as a human worker, it demonstrates how the use of robotics in agriculture may be expanded, even for crops like iceberg lettuce which are particularly challenging to harvest mechanically.
Crops such as potatoes and wheat have been harvested mechanically at scale for decades, but many other crops have to date resisted. Although it is the most common type of lettuce, iceberg is easily damaged and grows relatively flat to the ground, presenting a challenge for robotic harvesters.
“Every field is different, every lettuce is different,” said Simon Birrell from Cambridge’s Department of Engineering. “But if we can make a robotic harvester work with iceberg lettuce, we could also make it work with many other crops,” Birrell said.
“At the moment, harvesting is the only part of the lettuce life cycle that is done manually, and it’s very physically demanding,” said Julia Cai. The Vegebot first identifies the ‘target’ crop within its field of vision, then determines whether a particular lettuce is healthy and ready to be harvested.
It finally cuts the lettuce from the rest of the plant without crushing it so that it is ‘supermarket ready‘. “For a human, the entire process takes a couple of seconds, but it’s a really challenging problem for a robot,” said Josie Hughes, co-author of the study.