Robot chef is able to ‘taste’ food to make recipe improvements
Image credit: Dreamstime
A robot ‘chef’ has been trained by researchers from Cambridge University to assess the saltiness of a dish at different stages of the chewing process, imitating a similar process in humans.
They believe the 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.
The robot chef, which has already been trained to make omelettes based on human tasters’ 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.
“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 Grzegorz Sochacki, the paper’s first author. “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. “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.”
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 just 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, which are often time-consuming and only provide a single reading.
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 tweaked according to individual tastes.
“When a robot is learning how to cook, like any other cook, it needs indications of how well it did,” said Abdulali. “We want the robots to understand the concept of taste, which will make them better cooks. In our experiment, the robot can ‘see’ the difference in the food as it’s chewed, which improves its ability to taste.”
Dr Muhammad W Chughtai, senior scientist at Beko, which is collaborating on the project, said: “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.”
In future, the researchers are looking to improve the robot chef so it can taste different types of food and improve sensing capabilities so it can taste sweet or oily food, for example.
Sign up to the E&T News e-mail to get great stories like this delivered to your inbox every day.