human-language-accelerates-robotic-learning

A team of researchers at Princeton has found that human-language descriptions of tools can accelerate the learning of a simulated robotic arm that can lift and use various tools. The new research supports the idea that AI training can make autonomous robots more adaptive in new situations, which in turn improves their effectiveness and safety. By adding descriptions of a tool's form and function to the robot's training process, the robot's ability to manipulate new tools was improved. The new method is called Accelerated Learning of Tool Manipulation with Language, or ATLA. Anirudha Majumdar is an assistant professor of mechanical and aerospace engineering at Princeton and head of the Intelligent Robot Motion Lab.