Industrial robots provide the physical entities needed for embodied intelligence, enabling them to sense, manipulate, and move in the real world. The AI grand model provides a powerful "brain" for industrial robots, enabling them to have more advanced intelligence.
Unlike the current popular humanoid robots, embodied intelligent industrial robots are designed for industrial scenes and are more suitable for industrial production environments, rather than natural environments. The industrial environment is a relatively closed, simple environment with specific tasks and limitations, so there is no need for humanoid robots that are suitable for the natural environment.
With the diversification and individuation of market demand, the manufacturing industry will enter the era of "customized production". Traditional production lines often adopt a fixed production mode, which is difficult to adapt to changes. The addition of AI large models can make robots more flexible and can automatically adjust operation strategies and processes according to different production tasks, playing an important role in flexible manufacturing, which is especially important for manufacturing enterprises that need small and medium-sized batch and multi-variety production.
Intelligent industrial robots are developing step by step
Different production tasks have different production environments, embodied intelligent industrial robots must have a high degree of intelligence, in order to be able to flexibly switch between production tasks and adapt to different environmental needs.
Before the wave of generated AI, the industrial robot industry has adopted a large number of artificial intelligence technologies, such as incoming material detection, fault detection, product quality inspection and other links, and is still using traditional AI technologies such as computer vision.
However, traditional AI applications are only temporary and relatively low-cost solutions that are limited by data and computing power. In the future, with the continuous evolution of AI large models, it will be more widely used in all aspects of industrial production.
For example, in the field of handling palletizing applications, the worker teacher only needs to tap on the screen, and the industrial robot begins to automatically move the goods. In just a few minutes, a jumbled pile of containers was put into its proper place.
In the field of welding robot application, with the blessing of intelligent perception, machine vision and AI algorithm, industrial robots can independently identify weld position, adjust welding parameters, achieve weld tracking, and achieve high-quality and efficient welding operations without manual intervention throughout the process.
As a machine, with the progress of technology, the intelligent development of industrial robots is bound to be gradual. In the early stage, it will coexist with humans in the same production environment for a long time. With the development of technology, its degree of intelligence will become higher and higher, and more and more times will not need to collaborate with people to complete tasks independently. In the advanced stage of development, a true "unmanned factory" will be realized.
How to realize industrial robot intelligence
Although the integration of AI large models and robots has broad prospects, it still faces some challenges, how to let industrial robots soon have the ability to perform specific production tasks, or how to transfer human professional skills to industrial robots, the core is to achieve "intelligent flexible adaptation" through "environment perception", "human-computer interaction" and "learning optimization".
1. Environmental awareness
Traditional industrial robots need manual programming intervention when performing tasks, and also adopt manual teaching and other methods, while the AI large model emphasizes that the robot optimizes its behavior through its own perception and actions when performing tasks.
In order for robots to better interact with the environment, existing sensors need to be optimized and integrated first. For example, visual sensors (such as cameras, lidar, etc.) can help robots identify and locate objects; Force sensors allow the robot to sense the hardness and resistance of objects, thereby avoiding damage or collisions during handling and assembly.
2. Human-computer interaction
The core value of AI grand models is to enable people and devices to interact at the natural language level. Humans can communicate with robots in ways they are accustomed to, such as natural language, body language, actions, behavior demonstrations, etc., fundamentally breaking the semantic isolation between humans and machines. It establishes an efficient way of communication between human and machine, fundamentally breaks the barrier of man-machine communication, and changes the paradigm of man-machine interaction.
In order to achieve this, industrial robots need to have some natural language processing capabilities and emotion recognition capabilities, so that the robot can understand the instructions of the human operator and react accordingly. For example, robots can communicate with operators through voice recognition technology, get task instructions or feedback on work status, and even interact through non-verbal signals such as gestures and glances.
3. Learn to optimize
By integrating perception, cognition, and decision-making capabilities, AI grand models elevate robots from single-function executive units to intelligent systems with autonomous learning and optimization capabilities.
To achieve this, robots need to be equipped with advanced machine learning and deep learning algorithms. And constantly collect feedback data from the environment and itself, through these algorithms and data, the robot can identify potential improvement space from historical experience, constantly adjust its behavior, and optimize work efficiency.
In practice, enterprises can collect and process real-time data from the production line through the big data analysis platform, conduct in-depth analysis of the robot's behavior, and optimize its learning process and decision-making ability.
Conclusion
In general, the combination of artificial intelligence makes industrial robots more flexible and autonomous in the production process, improves production efficiency and quality, and can also reduce the threshold for the use of industrial robots, make industrial robot applications more popular, and stimulate more creative and innovative talents to enter the field of robotics, and promote the manufacturing industry to a new stage of intelligence and automation.
Robot Online believes that from the enterprise level, it can start from the practical application to explore the application scenarios of embodied intelligence in specific industries, such as intelligent manufacturing, warehousing and logistics, precise assembly and other fields. At the same time, pilot and deploy embodied intelligent robots as early as possible, accumulate practical experience, and promote the continuous optimization of technology. From the industrial chain level, intelligent hardware, software platform to service support and other aspects of common development, promote the transformation of embodied intelligent robots from a single function to a multi-functional platform, so that it can adapt to a wider range of industrial needs, forming an industrial ecosystem around embodied intelligent technology.
It can be predicted that embodied intelligence is becoming the key driving force for reshaping the competitive pattern of the global manufacturing industry, making the robot change from "active" to "own work", and providing support for the intelligent upgrade of the industrial manufacturing industry. Perhaps, who can seize the opportunity in this field, can be the first to break the game in the robot industry.
