In recent years, artificial intelligence (AI) has developed significantly in various fields such as natural language processing (NLP) and computer vision. However, one of the major challenges for AI is integrating it into the physical world. Although AI has performed well in reasoning and solving complex problems, these achievements are largely limited to digital environments. In order for AI to perform physical tasks through robotics, it must have a deep understanding of spatial reasoning, image manipulation and decision-making. To address this challenge, Google launched Gemini Robotics, a model used in robotics and embodies AI. Built on Gemini 2.0, these AI models incorporate advanced AI inference with the physical world, enabling robots to perform a variety of complex tasks.
Understand Gemini Robotics
Gemini Robotics is a pair of AI models built on Gemini 2.0, a state-of-the-art visual model (VLM) capable of processing text, images, audio and video. Gemini Robotics is essentially a VLM extension to the Visual Language-Action (VLA) model, which allows Gemini models to not only understand and interpret visual inputs and process natural language instructions, but also perform body movements in the real world. This combination is crucial for robotics, allowing machines to not only “see” their environment, but also understand it in the context of human language and perform the complex nature of real-world tasks, from simple object manipulation to more complex and flexible activities.
One of the key advantages of Gemini robotics is its ability to span various tasks without having to retrain a lot. The model can follow open vocabulary instructions, adapt to changes in the environment, and even handle unforeseen tasks that are not part of its initial training data. This is especially important for creating robots that can run in dynamic, unpredictable environments such as houses or industrial environments.
Reflected reasoning
A major challenge in robotics has been the gap between digital reasoning and physical interaction. While humans can easily understand complex spatial relationships and interact seamlessly with their surroundings, robots have been working hard to replicate these abilities. For example, robots have limited understanding of spatial dynamics, adaptation to new situations, and handling unpredictable real-world interactions. To address these challenges, Gemini robotics incorporates “embodied reasoning”, a process that allows systems to understand and interact with the physical world in a way similar to humans.
Contrary to AI reasoning in digital environments, embodied reasoning involves several key components, such as:
- Object detection and manipulation: The reflective reasoning allows Gemini robotics to detect and identify objects in their environment, even if they have not been seen before. It can predict where to grasp the object, determine its status and perform actions such as opening a drawer, pouring liquid or folding paper.
- Track and master predictions: Embodied reasoning allows Gemini Robotics to predict the most effective pathways of movement and determine the best points to hold objects. This feature is essential for tasks that require precise tasks.
- 3D Understanding: Embodied reasoning enables robots to perceive and understand three-dimensional space. This capability is especially important for tasks that require complex spatial operations, such as folding clothes or assembling objects. Understanding 3D also enables robots to perform well in tasks involving multi-view 3D communication and 3D bounding box prediction. These abilities may be crucial for robots to handle objects accurately.
Agility and adaptability: The key to real-world missions
Although object detection and understanding are crucial, the real challenge of robotics is to perform flexible tasks that require fine motor skills. Whether it’s folding origami fox or playing card games, tasks that require high precision and coordination usually go beyond what most AI systems do. However, Gemini Robotics is specially designed to excel in such tasks.
- Fine motor skills: The model’s ability to handle complex tasks such as folding clothes, stacking objects, or playing games demonstrates its advanced flexibility. Through other fine-tuning, Gemini robotics can handle tasks that require coordination across multiple degrees of freedom, such as complex operations using two arms.
- Almost no study:Gemini Robotics also introduces the concept of little learning, allowing it to learn new tasks with minimal demonstration. For example, Gemini Robotics can learn to perform tasks that may require a lot of training data in just 100 demonstrations.
- Novel implementations: Another key feature of Gemini robotics is its ability to adapt to new robotic embodiments. Whether it is a two-arm robot or a humanoid creature with tall joints, the model can seamlessly control various types of robot bodies, making it versatile and adaptable to different hardware configurations.
Zero beat control and quick adaptation
One of the outstanding features of Gemini robotics is its ability to control the robot in zero beats or several learning sessions. Zero shot control refers to the ability to perform tasks without the need for specific training for each task, while a few learning involves learning from a small number of examples.
- Generate zero-shooting controls through code: Gemini robotics can generate code to control robots even if they have never seen the specific action required before. For example, when providing an advanced task description, Gemini can create the required code to perform tasks by using its inference capabilities to understand physical dynamics and environments.
- Almost no study: If the task requires more complex agility, the model can also learn from the demonstration and immediately apply that knowledge to perform the task effectively. This ability to adapt quickly to new situations is a major advance in robotic control, especially for environments where continuous changes or unpredictability are required.
What the future means
Gemini robotics is an important advancement in general robotics technology. By combining AI’s inference capabilities with robots’ agility and adaptability, it brings us closer to the goal of creating robots that can be easily integrated into daily life and performing various tasks that require similar human interactions.
The potential applications of these models are broad. In an industrial environment, Gemini robotics can be used for complex assembly, inspection and maintenance tasks. In the family, it can help with chores, care and personal entertainment. As these models continue to evolve, robots may become a wide range of technologies that may open up new possibilities in multiple areas.
Bottom line
Gemini Robotics is a model suite built on Gemini 2.0, designed to enable robots to perform concrete reasoning. These models can help engineers and developers create AI-powered robots that understand and interact with the physical world in a human way. Gemini Robotics is able to perform complex tasks with high precision and flexibility, combining capabilities that embody reasoning, zero shooting control and a small amount of learning. These features allow the robot to adapt to its environment without the need for large-scale retraining. Gemini robotics has the potential to transform industries from manufacturing to home assistance, making robots more capable and safer in real-world applications. As these models continue to evolve, they have the potential to redefine the future of robotics.
