Robotics models connect vision, instruction understanding and action: they teach an arm to grasp objects and a mobile platform to navigate. This is a field for warehouses, manufacturing and research projects. Check which hardware the model supports, whether fine-tuning is needed and what the license allows.
A robot control model trained mostly on synthetic data from a world model. It reduces spending on collecting data from real robots.
"World" models for robots and self-driving vehicles: they generate realistic video of physical scenes and predict actions. Cosmos 3 combines understanding, generation and control.
A robot control model from Ant Group trained on a large volume of data from real robots. Version 2.0 works with different types of robot arms.
Open robot control models from Xiaomi. Robotics-1 is designed for household and kitchen tasks, U0 combines scene understanding and action.
A fully open robot control model that first "reasons" about space and trajectory, then acts. Its reasoning can be checked.
NVIDIA's foundation model for humanoid robots and robot arms: it sees, understands a command and outputs movements. Built into the Isaac ecosystem.
Robot control models from Physical Intelligence: folding laundry, tidying up, handling objects. π0.5 copes better in unfamiliar settings.
A small robot control model that runs on a regular laptop. Trained on open data from the LeRobot community, suited to low-cost robot arms.
The first large open vision-language-action model: a robot arm carries out commands like "put the apple in the bowl". OFT makes it several times faster.
An agent model that plans actions both in an interface (buttons on screen) and for a robot (arm movements). For now more of a research base than a finished product.
An open model can run on your own server: data stays in-house, there is no per-request fee, and the model can be fine-tuned on your documents.
