AI Startup Embodied Intelligence Wants Robots to Learn From Humans in Virtual Reality

We are building technology that enables existing robot hardware to handle a much wider range of tasks where existing solutions break down, for example, bin picking of complex shapes, kitting, assembly, depalletizing of irregular stacks, and manipulation of deformable objects such as wires, cables, fabrics, linens, fluid-bags, and food. To equip existing robots with these skills, our software builds on the latest advances in deep reinforcement learning, deep imitation learning, and few-shot learning, to all of which the founding team has made significant contributions. The result isn't just a new set of skills in the robot repertoire, but teachable robots, that can be deployed for new tasks on short turn-around. The background here will be familiar to anyone who has followed Abbeel's research at UC Berkeley's Robot Learning Lab (RLL).