Robot chef trained to develop a taste for seasoning

Working in collaboration with Beko, researchers from Cambridge University trained their robot chef to assess the saltiness of a dish at different stages of the chewing process, imitating a similar process in humans.

The texture and taste of food changes when it is chewed. The robot chef, already trained to make omelettes based on human taster’s feedback, tasted nine different variations 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 approach significantly improved the robot’s ability to quickly and accurately assess the saltiness of the dish over other electronic tasting technologies, which test a single homogenised sample. The team’s results are reported in Frontiers in Robotics & AI.

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“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,” said first author Grzegorz Sochacki from Cambridge’s Department of Engineering. “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.”

“When we taste, the process of chewing also provides continuous feedback to our brains,” said co-author Dr Arsen Abdulali, also from the Department of Engineering. “Current methods of electronic testing only take a single snapshot from a homogenised sample, so we wanted to replicate a more realistic process of chewing and tasting in a robotic system, which should result in a tastier end product.”

The researchers are members of Cambridge’s Bio-Inspired Robotics Laboratory run by Professor Fumiya Iida of the Department of Engineering, which focuses on training robots to carry out so-called last metre problems which humans find easy, but robots find difficult.

“We needed something cheap, small and fast to add to our robot so it could do the tasting: it needed to be cheap enough to use in a kitchen, small enough for a robot, and fast enough to use while cooking,” Sochacki said in a statement.

To imitate the human process of chewing and tasting in their robot chef, the researchers attached a conductance probe, which acts as a salinity sensor, to a robot arm. They prepared scrambled eggs and tomatoes, varying the number of tomatoes and the amount of salt in each dish.

Using the probe, the robot ‘tasted’ the dishes in a grid-like fashion, returning a reading in a few seconds.

To imitate the change in texture caused by chewing, the team then put the egg mixture in a blender and had the robot test the dish again. The different readings at different points of ‘chewing’ produced taste maps of each dish. Their results showed a significant improvement in the ability of robots to assess saltiness over other electronic tasting methods.

While their technique is a proof of concept, the researchers said that by imitating the human processes of chewing and tasting, robots will eventually be able to produce food that humans will enjoy and could be modified according to individual tastes.

“Beko has a vision to bring robots to the home environment which are safe and easy to use,” said Dr Muhammad W. Chughtai, senior scientist at Beko. “We believe that the development of robotic chefs will play a major role in busy households and assisted living homes in the future. This result is a leap forward in robotic cooking, and by using machine and deep learning algorithms, mastication will help robot chefs adjust taste for different dishes and users.”