OpenMind Aims to Be Android OS for Humanoid Robots

Silicon Valley-based startup OpenMind is developing a foundational software layer for humanoid robots, aiming to become the “Android operating system” of the robotics world. Unlike many companies focused on robot hardware, OpenMind specializes in the underlying software, known as OM1, designed to be open and hardware-agnostic.

According to OpenMind founder Jan Liphardt, a Stanford professor, while robots have long performed repetitive tasks, the advent of humanoids for home use and other human-to-machine interactions necessitates a new operating system that can “think more like a human.” Liphardt notes a significant shift in how machines can interact with people, emphasizing OpenMind’s view of itself as facilitating a collaboration between humans and machines.

On Monday, OpenMind unveiled FABRIC, a new protocol designed to enable robots to verify identity and share context and information with one another. Liphardt explained that unlike humans, machines can learn almost instantly. This capability, combined with improved inter-robot connectivity via FABRIC, will allow them to train and absorb new information more efficiently. He cited the example of robots sharing data on different languages, enabling them to interact with a wider range of people without direct human instruction for each language. Just as humans rely on infrastructure for communication and trust, Liphardt believes machines will require similar systems for coordination.

Founded in 2024, OpenMind is preparing to deploy its initial fleet of 10 OM1-powered robotic dogs by September. The company’s strategy emphasizes rapid iteration, with Liphardt anticipating extensive feedback from early users to quickly refine and improve the machines.

OpenMind recently secured $20 million in funding. The round was led by Pantera Capital, with participation from Ribbit, Coinbase Ventures, Pebblebed, and other strategic and angel investors. The company’s immediate focus is to get its technology into people’s homes, gather user feedback, and swiftly identify the most promising applications where current robotic capabilities align with human needs.