Take artificial intelligence industry development highland, Beijing as an example. The release of Beijing’s “Several measures” is the first special measure put forward by the local government in close contact with the industrial development of AI large model, and Beijing has fired the first shot of the local large model competition. At present, the “thousand model war” triggered by Chat-GPT is starting, and the large model may bring a new efficiency revolution and experience upgrade to all walks of life. With the action of Beijing, the first city of AI, Shanghai, Shenzhen, Chengdu and other regions have successively taken action to seize the “window period” of development.

Humanoid robots: The “unexpected encounter” between humans and machines

From the definition and purpose of use, a humanoid robot is an intelligent robot with a human-like appearance and movement. humanoid robots (humanoid robots), also translated as “humanoid robots”, literally means robots designed and manufactured to imitate the shape and behavior of humans. There is no universal definition of Humanoid Robots, but according to the book Humanoid Robots, humanoid robots should be able to “work in environments where people work and live, operate tools and equipment designed for people, and communicate with people.” Under this premise, humanoid robots should eventually have a human-like body structure, including a head, torso, and limbs, use bipedal walking, perform various operations with multi-fingered hands, and possess some degree of cognitive and decision-making intelligence.

Humanoid robots began in the late 1960s, with the most notable research results in Japan. In 1973, Professor Kato Ichiro of Waseda University in Japan developed the world’s first humanoid robot WABOT-1 WL-5 bipedal walking machine, strictly speaking, belongs to the bionic machinery, is the prototype of humanoid robots. In 1986, Japan’s Honda began research on the humanoid robot ASIMO, and successfully released the first generation model in 2000.

4. Humanoid robots and AI large models: Universal scenarios accelerate the revolutionary advancement of the C-end

With the continuous breakthrough of key technologies such as integrated design technology, motion management and control technology, and sensor perception technology, as well as the continuous integration and application of new generation information technologies such as artificial intelligence and 5G, special robots are accelerating their application in coal mines, deep sea, polar and other scenes, releasing huge production and scientific research value. Among them, what most makes cutting-edge technology companies and ordinary consumers “fascinated” is the emergence and iteration of intelligent mobile robots represented by humanoid robots.

At present, AI technology makes it possible for robots to operate autonomously by building intelligent systems with comprehensive perception, real-time interconnection, analysis and decision-making, and autonomous learning. AI strengthens the robot’s perception ability through robot vision technology, and improves its ability to analyze and make decisions and learn independently by building an algorithm model, so that the robot can complete tasks independently.

1. The ability to perceive the world (robot eyes)

Laser and visual navigation are the main applications in the sensing and positioning technology of robot autonomous movement. The development of computer vision has experienced the traditional vision methods represented by feature descriptors and the deep learning technology represented by CNN convolutional neural network. At present, the general vision large model is in the research and exploration stage. The scene of humanoid robot is more general and complex than that of industrial robot. The multi-task training scheme of All in One vision model can make the robot better adapt to the human life scene.

On the one hand, the strong fitting ability of large models enables humanoid robots to have higher accuracy in target recognition, obstacle avoidance, three-dimensional reconstruction, semantic segmentation and other tasks. On the other hand, the large model solves the problem that deep learning technology relies too much on the data distribution of a single task, and the scene generalization effect is poor. The general vision large model learns more general knowledge through a large amount of data and migrates to downstream tasks. The pre-trained model obtained based on massive data has better knowledge completeness and improves the scene generalization effect.

Typical product: Tesla “Optimus”

At the perceptual level, the Tesla robot head uses eight cameras to collect visual information. At the computational level, the robot will use the FSD (Full Self-Driving) computer used by Tesla cars at present, and use neural networks and other models to process information in real time. Tesla will use the supercomputer “Dojo” to train the AI model used by the robot to recognize and react to external objects more efficiently.