Smart robots to make a salad

Having a robot pick a bunch of grapes requires a lot of technology. But it can be even more challenging: a robot making a complete, ready-to-eat salad. The Wageningen University & Research Agro Food Robotics programme researchers face this challenge in the coming five years. ?It is now technologically possible.? Typical main-course salads you can buy in a supermarket contain lettuce, raw vegetables, pasta, potatoes, fruit, nuts, eggs, cheese, meat and fish. To date, there is no option to automatically gather and package all these different products without the input of human labour. WUR experts in computer vision, robotics and AI want to change that in the coming five years in collaboration with industrial partners. Successful development of such a machine would save a lot of line workers, which, in turn, saves costs in an increasingly shallow labour pool. To automatically prepare and package a main-course salad, robots must perform all tasks performed when single products are packaged. Cameras take pictures for advanced computer programmes that learn to recognise products. Then, the same software is used to drive robotic arms that remove products rapidly without damaging them from the harvest crates and deposit them in custom packaging. The packaging is then sealed, and the product information is printed on it. Artificial intelligenceThe technology that the researchers will develop further is built upon the results from the ?Pick?nPack? project led by WUR from 2011 till 2016. ?At the time, producers were not exactly lining up to obtain the Pick?nPack technology, but that is beginning to change?, says Paul Goethals, business development manager in the WUR Agro Food Robotics programme. Not only has the shortage of labour increased the demand, but the technology has also been developed further and is now cheaper, says Goethals. This is mainly due to the advancements in Artificial Intelligence (AI). ?AI is making applications such as this more relevant for businesses.? ?Before, we would have to feed the software with characteristics with which to analyse the camera images. Now, we use machine learning with training data. This serves as input for the software to autonomously recognise particular properties of vegetables?, Goethals explains. ?That then helps the robots recognise and grab the products directly from the harvest crates, without humans first having to deposit the goods on the production line. The stacked products are often easily bruised.? This means that the robots must be very precise.Source and full post