A robot ‘chef’ has been trained to taste food at different stages of the chewing process to assess whether it’s sufficiently seasoned.
Working in collaboration with domestic appliances manufacturer Beko, researchers from the University of Cambridge trained their robot chef to assess the saltiness of a dish at different stages of the chewing process, imitating a similar process in humans.
Their results could be useful in the development of automated or semi-automated food preparation by helping robots to learn what tastes good and what doesn’t, making them better cooks.
When we chew our food, we notice a change in texture and taste. For example, biting into a fresh tomato at the height of summer will release juices, and as we chew, releasing both saliva and digestive enzymes, our perception of the tomato’s flavour will change.
The robot chef, which has already been trained to make omelettes based on human taster’s feedback, tasted nine different variations of a simple dish of scrambled eggs and tomatoes at three different stages of the chewing process, and produced ‘taste maps’ of the different dishes.
The researchers found that this ‘taste as you go’ approach significantly improved the robot’s ability to quickly and accurately assess the saltiness of the dish over other electronic tasting technologies, which only test a single homogenised sample. The results are reported in the journal Frontiers in Robotics & AI.
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