Researchers Score Loot To Build Teachable Robots

Embodied Intelligence, a company working to democratize robotics by enabling anyone to teach a robot new skills, has raised $7 million in seed funding. The capital will be used to develop AI software, a.k.a. robot brains, that’s loadable onto existing robots and makes it easy to teach them complex skills.


While traditional programming of robots requires writing code, Embodied Intelligence software will empower anyone to program a robot by simply donning a VR headset and guiding a robot through a task. These human demonstrations train deep neural nets, which are further tuned through the use of reinforcement learning, resulting in robots that can be easily taught a wide range of skills in areas where existing solutions break down.


Complicated tasks like the manipulation of deformable objects such as wires, fabrics, linens, apparel, fluid-bags, and food; picking parts and order items out of cluttered, unstructured bins; completing assemblies where hard automation struggles due to variability in parts, configurations, and individualization of orders, are all candidates to benefit from Embodied Intelligence’s work.


The founding team behind Embodied Intelligence has a combined 30 years of experience in artificial intelligence, deep learning and robotics. Abbeel’s lab at UC Berkeley has pioneered many recent breakthroughs in robot learning, including a robot that organizes laundry, robots that learn (simulated) locomotion, robots that learns vision-based manipulation from their own trial and error and from human VR teleop. Founders Pieter Abbeel, Peter Chen and Rocky Duan recently spent over a year at OpenAI, pushing the frontier in deep imitation learning, reinforcement learning, unsupervised learning, and learning-to-learn. For more details, contact Embodied Intelligence.