Captures live video of warehouse shelves
AI Models & Assistants / Knowledge library
gemini robotics er 2 preview
Gemini family endpoint. Consult the linked model catalog for exact modalities, thinking settings, lifecycle and limits.
Why learn gemini robotics er 2 preview?
Offers the documented Google model capabilities through hosted.
The problem it solves
Provides model inference for supported documented inputs.
Where it came from
gemini robotics er 2 preview: Gemini family endpoint. Consult the linked model catalog for exact modalities, thinking settings, lifecycle and limits. Published aliases: gemini-robotics-er-2-preview. Input: consult source. Output: consult source. Checked 2026-10-13. Model capabilities are distinct from tools available in a particular agent.
Build your understanding
Work through these exercises in order. Try the task before opening a reference.
- Explain what gemini robotics er 2 preview does.
- Identify a use case for gemini robotics er 2 preview.
- Describe a limitation of gemini robotics er 2 preview.
- Name a compatible tool for gemini robotics er 2 preview.
- Compare gemini robotics er 2 preview against an alternative.
Documentation and sources
- Primary source / model card (ai.google.dev)
Catalog research notes
- See the AI Workbench for source dates, pricing evidence and configuration details.
Connect the ideas
Built on
Real World Example
Autonomous Warehouse Inventory Reconciliation
Large-scale logistics providers managing high-density automated storage and retrieval systems.
The business problem
Traditional robotic systems struggle with spatial ambiguity and multi-step tool orchestration when items are misplaced or stacked irregularly, leading to manual intervention costs.
How this topic solves it
Gemini Robotics ER 2 Preview provides advanced video understanding and spatial reasoning, allowing robots to interpret complex physical environments and coordinate multi-step tasks to resolve inventory discrepancies autonomously.
- Integrate the gemini-robotics-er-2-preview endpoint into the robot's onboard perception stack.
- Stream real-time video feeds from robot-mounted cameras to the model for spatial analysis.
- Define high-level task goals such as identifying and re-organizing misplaced inventory items.
- Execute multi-step tool orchestration commands generated by the model to manipulate objects.
- Validate task completion through continuous visual feedback loops.
The flow shows how the robot perceives the environment and uses the model to act.
Processes video for spatial reasoning
Translates reasoning into motor commands
Performs the movement
- Robot Camera → sends video stream → Gemini Robotics ER 2
- Gemini Robotics ER 2 → outputs task plan → Orchestrator
- Orchestrator → triggers action → Physical Actuator
Expected business outcome
Increased operational autonomy in complex, dynamic warehouse environments with reduced reliance on human oversight for routine spatial problem-solving.
Limitations and checks
The model's reliance on high-fidelity video processing may introduce latency in decision-making; developers should monitor the inference time against the physical robot's control loop frequency to ensure safety.