As robots make their way into a variety of real-world environments, roboticists are trying to ensure that they can efficiently complete a growing number of tasks. For robots that are designed to assist humans in their homes, this includes household chores, such as cleaning, tidying up and cooking. By Ingrid Fadelli , Tech Xplore.
Stir-fry, the cooking style that the team focused on in their recent paper, involves complex bimanual skills that are difficult to teach to robots. To effectively do this, Liu and his colleagues first tried to train a bimanual coordination model known as a “structured-transformer” using human demonstrations.
Researchers at the Idiap Research Institute in Switzerland, the Chinese University of Hong Kong (CUHK) and Wuhan University (WHU) have recently developed a machine learning-based method to specifically teach robots to master stir-fry, the Chinese culinary cooking technique. Their method, presented in a paper published in IEEE Robotics and Automation Letters, combines the use of a transformer-based model and a graph neural network (GNN).
Food preparation and cooking are two crucial activities in the household, and a robot chef that can follow arbitrary recipes and cook automatically would be practical and bring a new interactive entertainment experience. The researchers assessed their model’s performance both in simulations and on a physical two-handed robotic platform, known as the Panda robot. In these tests, their model allowed the robot to successfully and realistically reproduce the motions involved in stir-fry. Interesting read!
[Read More]