Google DeepMind unveils Gemini Robotics 2 with full-body control

DeepMind's earlier Gemini Robotics models focused on upper-body manipulation for tabletop tasks—a significant but narrow application. Gemini Robotics 2 extends that capability to the entire robot body, enabling tasks that require coordinated walking, crouching, reaching, and precise manipulation. This shift is important because real-world household and workplace tasks rarely involve only stationary, arm-only actions; they require movement through space and dexterous interaction with objects in variable layouts.

The introduction of Gemini Robotics ER 2 as a separate reasoning layer adds another layer of capability. Rather than controlling moment-to-moment actions, this model acts as a "high-level brain" that understands multi-step task sequences lasting several minutes and involving hundreds of decisions. It communicates with humans, observes context, self-corrects when steps fail, and—for the first time in DeepMind's robotics line—enables multiple robots to work together. The ability to track when tasks begin and end represents a measurable step forward in how robots understand progress.

The on-device variant addresses a practical constraint: many robotic applications cannot rely on network connectivity or tolerate latency. By running locally and adapting to new embodiments in hours rather than days or weeks, Gemini Robotics On-Device 2 lowers the barrier to deploying physical AI in settings where internet access is unreliable. DeepMind's introduction of ASIMOV-Agentic, a safety benchmark for agentic orchestration, signals that the company is building guardrails alongside capability—measuring both refusal of unsafe actions and proactive requests for human intervention when uncertainty arises.