Novel framework can create egocentric human demonstrations for imitation learning
One of the most promising approaches to teaching robots how to complete manual tasks such as cleaning dishes or preparing food is known as imitation learning. End-to-end imitation learning typically entails training a deep learning algorithm on raw videos, images and/or motion capture data of humans completing manual tasks.
Robots that can closely imitate the actions and movements of humans in real-time could be incredibly useful, as they could learn to complete everyday tasks in specific ways without having to be extensively pre-programmed on these tasks. While techniques to enable imitation learning considerably improved over the past few years,…
A collaboration between NVIDIA and academic researchers is prepping robots for surgery. ORBIT-Surgical — developed by researchers from the University of Toronto, UC Berkeley, ETH Zurich, Georgia Tech and NVIDIA — is a simulation framework to train robots that could augment the skills of surgical teams while reducing surgeons’ cognitive…
From wiping up spills to serving up food, robots are being taught to carry out increasingly complicated household tasks. Many such home-bot trainees are learning through imitation; they are programmed to copy the motions that a human physically guides them through.