Figure founder and CEO Brett Adcock Thursday revealed a new machine learning model for humanoid robots. The news, which arrives two weeks after Adcock announced the Bay Area robotics firm’s decision to step away from an OpenAI collaboration, is centered around Helix, a “generalist” Vision-Language-Action (VLA) model.
VLAs are a new phenomenon for robotics, leveraging vision and language commands to process information. Currently, the best-known example of the category is Google DeepMind’s RT-2, which trains robots through a combination of video and large language models (LLMs).
Helix works in a similar fashion, combining visual data and language prompts to control a robot in real time. Figure writes, “Helix displays strong object generalization, being able to pick up thousands of novel household items with varying shapes, sizes, colors, and material properties never encountered before in training, simply by asking in natural language.”
Image Credits:Figure
In an ideal world, you could simply tell a robot to do something and it would just do it. That is where Helix comes in, according to Figure. The platform is designed to bridge the gap between vision and language processing. After receiving a natural language voice prompt, the robot visually assesses its environment and then performs the task.
Figure offers examples like, “Hand the bag of cookies to the robot on your right” or, “Receive the bag of cookies from the robot on your left and place it in the open drawer.” Both of these examples involve a pair of robots working together. This is because Helix is designed to control two robots at once, with one assisting the other to perform various household tasks.
Figure is showcasing the VLM by highlighting the work the company has been doing with its 02 humanoid robot in the home environment. Houses are notoriously tricky for robots, given they lack the structure and consistency of warehouses and factories.
Difficulty with learning and control are major hurdles standing between complex robot systems and the home. These issues, along with five- to six-digit price tags, are why the home robot hasn’t taken precedence for most humanoid robotics companies. Generally speaking, the approach is to build robots for industrial clients, both improving reliability and bringing down costs …