Robot chef imitates human eating process as it learns to taste food to assess the saltiness of dish

With artificial intelligence (AI) and robotics becoming a common practice, scients are stepping up the game, making robots come as close to reality as possible. As such, researchers from the University of Cambridge have now trained their ‘robot chef’ to assess the saltiness of a dish at different stages of the chewing process, just like humans.
Their results could be useful in the development of automated or semi-automated food preparation helping robots learn what tastes good and what doesn’t, making them better cooks.

As part of the research, the robot chef, which has already been trained to make omelettes based on a 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. Additionally, it produced ‘taste maps’ of different dishes.
The researchers found the ‘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.
“Most home cooks will be familiar with the concept of tasting as you go — checking a dish throughout the cooking process to check whether the balance of flavours is right. If robots are to be used for certain aspects of food preparation, it’s important that they are able to ‘taste’ what they’re cooking,” said Grzegorz Sochacki from Cambridge’s Department of Engineering, the paper’s first author.
Co-author Dr Arsen Abdulali added: “When we taste, the process of chewing also provides continuous feedback to our brains. Current methods of electronic testing only take a single snapshot from a homogenised sample, so we wanted to replicate a more realic process of chewing and tasting in a robotic system, which should result in a tastier end product.”
To enable the robot chef to chew and taste food, the researchers attached a conductance probe – which acts as a salinity sensor – to a robot arm. Using the probe, the robot ‘tasted’ the dishes in a grid-like fashion, returning a reading in just a few seconds.

Further, to imitate the change in texture caused chewing, they put the egg mixture in a blender and had the robot chef test the dish again. The different readings at different points of ‘chewing’ produced taste maps of each dish.
This development, according to the researchers, will help robots to prepare foods as per the liking and preferences of humans.
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