Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory have developed a predictive AI model that allows a KUKA robot arm to learn to identify objects by touch and sight. The system is based on the work of MIT graduate student Jiwon Kim, who has been working with computer vision researchers in Korea for several years. The team said its model was restricted to working in a controlled environment and it aimed to switch to unstructured areas or possibly use an MIT-designed tactile glove to expand the data set.
Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory have developed a predictive AI model that allows a KUKA robot arm to learn to identify objects by touch and sight. The team used an MIT-created sensor called GelSight and a web camera to build a data set of more than three million visual and tactile-paired images, called VisGel. The team said its model was restricted to working in a controlled environment and it aimed to switch to unstructured areas or possibly use an MIT-designed tactile glove to expand the data set.