Robot chef has learned to taste and evaluate the taste of food while cooking

(ORDO NEWS) — The researchers trained a robotic chef to taste food during cooking, mimicking the process of chewing.

The method made it possible to accurately and quickly estimate the amount of salt in a dish, as well as to draw up “taste maps”, which brought the work of the robot’s sensors closer to human perception.

Scientists from the University of Cambridge (UK), in collaboration with the manufacturer of household appliances Beko, trained a robot chef to evaluate the saltiness of a dish at different stages of cooking.

Prior to this, the robot had already been able to cook an omelette based on feedback from tasters. Now he was able to taste the food himself, imitating the process of chewing and compiling a “taste map”.

The results of the study, published in the journal Frontiers in Robotics & AI, will be relevant to the creation of methods for automated or semi-automated food preparation.

In addition, the new approach significantly accelerated the assessment of food salinity compared to traditional methods.

Taste perception is a complex process that is influenced by the appearance, smell, texture, and temperature of food.

The saliva produced during chewing helps carry chemicals to the taste buds that send signals to our brains. At the same time, the taste changes as the food is chewed, which provides constant feedback to the brain.

Often we taste the dish during the cooking process to appreciate its taste. Existing e-tasting methods rely on the analysis of a single homogenized sample. Therefore, scientists sought to reproduce a more realistic process of taste perception in a robotic system.

To do this, the researchers attached a salinity sensor to the robot’s arm. As the egg and tomato dish cooked, he “tasted” the food, taking readings in just a few seconds.

To mimic the texture change that occurs when chewing, the scientists put the food pieces into a blender, and the robot reevaluated the taste. Readings collected at various moments of grinding food in a blender allowed him to create “taste cards” of each dish.

By mimicking human perception of taste, robots can learn how to cook food that people like and adapt to their individual preferences. Understanding the concept of taste will make robots better cooks.

Such devices will be in demand in nursing homes, boarding schools, hospitals and other organizations where human resources are not always enough to provide all people with tasty and balanced meals.

In the future, the authors plan to equip the robot with other sensors that will allow it to evaluate the fat content of food, as well as distinguish between sweet and sour taste.

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