Handles complex instructions locally with just 50–100 task demonstrations.
Tested on multiple robot types, including humanoid and industrial arms.
Prioritizes semantic and physical safety, guided by Google’s internal standards.
Google has formally unveiled a new iteration of Gemini AI that can function solely on robotic hardware and doesn’t require an internet connection. The model, called Gemini Robotics On-Device, provides task generalisation and fine tuning with minimal data, and it gives bi-arm robots local, low-latency control.
SurveyThe Gemini Robotics On Device handles language, action, and vision inputs on the device itself, in contrast to cloud-dependent models. This might be helpful in places like manufacturing floors or remote settings where latency needs to be kept to a minimum or connectivity is restricted. Google claims that the model can follow natural language instructions and learn from just 50 to 100 demonstrations to accomplish tasks like zipping bags, folding clothes, and pouring liquids.
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Specifically designed as a lightweight extension of the Gemini 2.0 architecture, the on-device version preserves multi-step reasoning and dexterous control while optimising for smaller compute footprints. Having been successfully tested on robots other than its initial training setup, such as the Apptronik Apollo humanoid and the bi-arm Franka FR3, it also facilitates rapid adaptation to new tasks or robotic forms.
Through a reliable testing program, Google is also providing a Gemini Robotics SDK to a select group of developers. Users can test the model in MuJoCo physics simulations and adjust it for particular tasks using this SDK. Access is still restricted, though, while the business assesses its effectiveness and security in actual environments.
Google claims that with extra safety precautions in place, the development is consistent with its internal AI Principles. These consist of benchmarking for semantic integrity and low-level controllers for physical safety. Under the direction of the company’s Responsibility & Safety Council, the system is being assessed using a new semantic safety benchmark.
Google is indicating a move towards more autonomous and locally adaptable robotics systems with the on-device model, which could have repercussions for logistics, industrial automation, and other areas.
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Ashish Singh
Ashish Singh is the Chief Copy Editor at Digit. He's been wrangling tech jargon since 2020 (Times Internet, Jagran English '22). When not policing commas, he's likely fueling his gadget habit with coffee, strategising his next virtual race, or plotting a road trip to test the latest in-car tech. He speaks fluent Geek. View Full Profile
