Google Deepmind's Gemini Robotics-ER 1.6 gives robots a sharper brain for planning and perception

2026-04-17 · Source: The Decoder · Field: Technology & Digital — Robotics & Autonomous Systems, Artificial Intelligence & Machine Learning · Depth: Intermediate, quick

Summary

Google Deepmind has released Gemini Robotics-ER 1.6, an enhanced model designed for embodied reasoning in robots. This upgrade functions as a high-level cognitive layer, enabling robots to better comprehend their environment and autonomously plan tasks, integrating tools such as Google Search or vision-language-action models as needed. Deepmind reports that version 1.6 outperforms its predecessor, Gemini Robotics-ER 1.5, and Gemini 3.0 Flash in tasks like object pointing, counting, and recognizing successful task completion. A significant improvement, developed with Boston Dynamics, is the model's ability to read instruments like pressure gauges and sight glasses, achieved by combining agentic image processing with code execution to interpret detailed readings.

Key takeaway

For robotics engineers developing autonomous systems, Gemini Robotics-ER 1.6 offers significant advancements in robot perception and task planning. You should explore its capabilities for applications requiring precise instrument reading or complex environmental understanding, potentially reducing manual programming for specific tasks. Consider leveraging the provided Colab example to quickly prototype and integrate this model into your existing robot platforms.

Key insights

Gemini Robotics-ER 1.6 enhances robot autonomy through improved perception, planning, and instrument reading capabilities.

Principles

• Embodied reasoning improves robot task execution.
• Agentic image processing enhances visual interpretation.

Method

The model uses agentic image processing to zoom into details, applies pointing functions and code for calculations, and then uses world knowledge to interpret instrument readings.

In practice

• Integrate Gemini Robotics-ER 1.6 via Gemini API.
• Utilize Colab example for developer onboarding.

Topics

• Gemini Robotics-ER 1.6
• Embodied Reasoning
• Robot Perception
• Task Planning
• Instrument Reading

Code references

• google-gemini/robotics-samples

Best for: Machine Learning Engineer, Computer Vision Engineer, Robotics Engineer, AI Engineer

Related on AIssential

• Gemini Robotics-ER 1.6: Powering real-world robotics tasks through enhanced embodied reasoning — Gemini Robotics-ER 1.6 enhances robot autonomy through advanced spatial reasoning, multi-view understanding, and instrument reading.
• Gemini Robotics ER-1.6 enhances reasoning to help robots navigate real-world tasks. — Gemini Robotics-ER 1.6 enhances robot autonomy through improved spatial reasoning and new instrument reading capabilities.
• Boston Dynamics’ robot dog now reads gauges and thermometers with Google's AI — Google DeepMind's Gemini Robotics-ER 1.6 model significantly enhances robot perception and safety for complex industrial inspections.
• Powering the future of robotics in Europe — Google DeepMind's accelerator empowers European robotics startups with AI models and expertise to develop real-world physical AI solutions.
• Google Deepmind's Gemini Robotics models will power Boston Dynamics' Atlas for industrial tasks — Google Deepmind's Gemini Robotics models will power Boston Dynamics' Atlas robots for industrial automation.
• ​Boston Dynamics and Google DeepMind Teach Spot to Reason​ — Integrating advanced AI reasoning models into robots enhances autonomy for complex real-world tasks.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by The Decoder.