Google DeepMind says Gemini Robotics 2 enables full body control

Google — deepMind says Gemini Robotics 2 can control the five-fingered, 22 degree-of-freedom SharpaWave hand on Apptronik’s Apollo 2 humanoid. | With the first version, the company showed how Gemini’s multimodal understanding could drive real-world action.

The updated version includes intelligent whole-body control, advanced dexterity, and multi-robot collaboration, DeepMind said. Gemini Robotics 2 enables robots to reason through every movement, unlocking a broad range of tasks. For example, it could enable a humanoid to walk, crouch, stretch, and manipulate objects to clean up a cluttered room. The robot could also team up with other robots to finish the job faster. Gemini Robotics 2 can also run locally on-device while adapting to entirely new robotic bodies in just a few hours, claimed DeepMind. In addition to the VLA, the company also released: Gemini Robotics ER 2: This embodied reasoning (ER) model is a vision language model (VLM) that acts as DeepMind’s agent, enabling robots to communicate with people, understand the physical world, and plan multi-step tasks lasting several minutes. DeepMind is also introducing the ability for robots to work together as a team. Gemini Robotics On-Device 2: The company optimized this VLA to run locally on robotic devices. The model can now achieve fast adaptation to completely new robot embodiments with a few hours of data, DeepMind said. Gemini Robotics ER 2 is now available on Google AI Studio and in private preview on Gemini Enterprise Agent Platform. The VLA and On-Device models are available to early-access partners. Gemini Robotics 2 manages the entire robot body DeepMind’s previous models controlled the humanoid’s upper body to achieve tabletop tasks. Now, Gemini Robotics 2 is expanding physical AI into whole-body motions. The model can now control entire humanoid robots, translating intent into intelligent whole-body control. For example, when controlling Apptronik‘s Apollo 2 humanoid robot, users can ask it to “put the watering can into the green bin in the bottom shelf.” Apollo processes the instruction, walks to the table, and picks up the watering can, takes a few steps to the shelves, and places it precisely in its destination.