Handling soft fruit is tricky for robots, but after training with hours of data from a human operator, a machine learning algorithm developed the motor skills needed to peel a banana 57 per cent of the time.
Researcher Heecheol Kim explained that developed a machine learning mimicking system that trained the robots in manual dexterity. This required several hours of human training.
First, a human operating the robot peeled hundreds of bananas, creating 811 minutes of demonstration data to train the robot to do it by itself. The task was divided into nine stages, from grasping the banana to picking it up off the table with one hand, grabbing the tip in the other hand, peeling it, then moving the banana so the rest of the skin can be removed.
As the video shows, the robots go into reactive mode, holding the banana at advantageous angles in order to get the task done.
But when the arms are required to precisely manipulate the banana, the system switches to a reactive approach, where it responds to unexpected changes in its environment.