Smart Agricultural Technology

Researchers have developed a new way to generate realistic synthetic training data for agricultural robots by recreating tomato cultivation environments in a virtual world. The approach could help overcome one of the biggest barriers in agricultural robotics: the time and labor required to collect and manually label real-world data under challenging greenhouse conditions such as changing lighting, dense foliage, and fruit occlusion.

A scientist has solved the conundrum of why robots struggle to pick tomatoes