In a major development in robotics, Boston Dynamics has enhanced its quadruped robot Spot by integrating Google DeepMind’s Gemini Robotics-ER 1.6 model. The upgrade aims to improve the robot’s intelligence and efficiency in handling complex real-world tasks.
The collaboration is focused mainly on industrial inspection, where legged robots like Spot are already being widely used for practical applications.
With the new integration, Spot can now autonomously detect hazardous debris or spills and read complex gauges and sight glasses. It can also use advanced tools like vision-language-action models when it needs help interpreting its surroundings.
According to Marco da Silva, VP and GM of Spot at Boston Dynamics, this upgrade marks a significant step toward robots that can better understand and operate in the physical world.
The concepts of “reasoning” and “understanding” are central to this advancement. Carolina Parada, head of robotics at Google DeepMind, explained that true understanding is measured by whether a system can respond in a human-like way. This ability is important for ensuring safe and reliable task execution.
Safety remains a key focus. Parada said Gemini Robotics-ER 1.6 is designed to approach tasks from a safety-first perspective, preventing robots from taking risky actions. While the current version of Spot does not yet apply these safety models to object handling, future versions are expected to improve in this area.
Training such AI systems remains a challenge. Since physical interaction data is limited, current models rely mainly on vision-based learning. To improve performance, customers using Spot for inspections will need to share data with Boston Dynamics, helping build more diverse training datasets.
This upgrade represents an important step toward making robots more capable, reliable, and safe in real-world environments.
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