Driven by a shortage of skilled workers and increasing wages worldwide, robotics researchers and horticultural growers are partnering to develop robots that enhance the productivity of the human workforce.
Discerning robotic vision is key when designing a picking or harvesting robot. Improvements in machine-vision algorithms and the use of multi-spectral cameras are helping the latest robots to find their targets in a crop much faster. Early bots designed at the Dutch horticultural research facility at Wageningen University chose to start with yellow peppers, what one could call the ‘low hanging fruit’. Teaching a camera on a robot to find yellow or red peppers in a leafy green crop is relatively simple compared to the task that Farshid Amirabdollahian, professor of human-robot interaction at the University of Hertfordshire, set himself.
Finding green fruits
Working with one of the largest growers of cucumbers in the UK, his robots had to learn to find a green fruit often partially masked by green leaves. He equipped his robot with a stereo camera that is also sensitive to infrared light, which provides more textural information, helping the robot to differentiate between fruit and leaf. “Training the machine-learning algorithm is painstaking and laborious, involving hand-labelling thousands of images,” he says.
Considering that skilled humans can pick a cucumber every 3-4 seconds, it would seem that the human workforce has little to worry about, but Amirabdollahian and his commercial grower partner, Glinwell (a supplier to Tesco), calculate that a robot has only to get down to 10 seconds per fruit to compete, as it will be able to work for 16 hours a day or more. It is also possible that robots could work slowly through the night.
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