A team of engineers have trained a Chef robot to prepare an omelette, all the way from cracking the eggs to plating the finished dish, and refined the ‘chef’s’ culinary skills to produce a reliable dish that actually tastes good.
The researchers, from the “University of Cambridge” in collaboration with the domestic appliance company Beko, used “Machine learning” to train the robot to account for highly subjective matters of taste. The results are reported in the journal “IEEE Robotics and Automation Letters”, and will be available online as part of the virtual IEEE International Conference on “Robotics and Automation” (ICRA 2020).
A robot that can cook has been an aspiration of sci-fi authors, futurists, and scientists for decades. As “Artificial intelligence” techniques have advanced, commercial companies have built prototype robot chefs, although none of these are currently commercially available, and they lag well behind their human counterparts in terms of skill.
“Cooking is a really interesting problem for “Roboticists”, as humans can never be totally objective when it comes to food, so how do we as scientists assess whether the robots has done a good job?” said “Dr Fumiya Iida” from Cambridge’s Department of Engineering, who led the research.
Teaching a robot to prepare and cook food is a very challenging task, since it must deal with complex problems in robot manipulation, computer vision, sensing and human-robot interaction, and produce a consistent end product.
In addition, taste differs from person to person — cooking is a qualitative task, “while robots generally excel at quantitative tasks”. Since taste is not Universal, universal solutions don’t exist. Unlike other optimisation problems, special tools need to be developed for robots to prepare food.