Following the big model, "embodied intelligence" has become a new hot spot in the technology industry this year and is considered to be the key direction in the new wave of artificial intelligence (AI). Many start-ups have emerged, financing has hit new highs, and technology has continued to break through... As the most representative entity in this field, humanoid robots are accelerating industrialization under the catalysis of big models.
If big models are regarded as "interesting souls", humanoid robots enabled by "embodied intelligence" have "good-looking skins" and have become powerful assistants for humans in many fields.
Redefining robots
As a bridge connecting virtual space and real space, "embodied intelligence" refers to the integration of AI into physical entities such as robots, giving them the ability to perceive, learn and dynamically interact with the environment like humans.
The term "embodied intelligence" itself has a strong philosophical color of technology. In 1945, French philosopher Maurice Merleau-Ponty proposed the concept of "embodiment", believing that humans need to interact and perceive the surrounding environment through their bodies in order to understand the world. In 1950, British computer scientist Turing, known as the "father of AI", first proposed the concept of "embodied intelligence" in his paper "Computing Machinery and Intelligence".
In fact, industrial robots (robotic arms) with relatively low intelligence levels have long been widely used in the manufacturing industry, bringing about quality and efficiency improvements. However, traditional industrial robots are a combination of "fixed programs + robotic arms", while robots empowered by "embodied intelligence" are an iteration of "multimodal perception + brain decision-making".
Xu Huazhe, assistant professor at the Institute of Cross-Disciplinary Information Sciences of Tsinghua University, believes that robots in the future will present a variety of forms: bipedal, quadrupedal, wheeled, mechanical dogs, intelligent drones and even mechanical bees, but humanoid robots are the most adaptable to human society and will become the robots that can best help humans.
Humanoid robots can solve the problem of the "last mile" of the production line. Many personalized and customized products cannot be assembled uniformly on the assembly line, which requires humanoid robots with generalization capabilities to "help" assemble mass-produced parts into products according to customer customization needs. In more complex and changeable scenarios such as home services and public services, humanoid robots also have more advantages and can adapt to different environments and needs to complete a variety of tasks.
Three major difficulties to be overcome
The development of humanoid robots begins with learning and imitating humans. The difficulties in its development can also be understood by comparing it with the human brain, cerebellum and body. The "brain" is mainly responsible for the robot's autonomous learning, planning and decision-making center; the "cerebellum" is responsible for motion control, including walking to running and jumping, and from simple grasping to complex hand movements; and the "body" includes the trunk and limbs structure and dexterous hand design.
UBTECH Robotics Vice President and Research Institute Director Jiao Jichao told reporters that there are many technical difficulties to be overcome in these three major areas: In terms of the "brain", cloud-edge-end integrated computing architecture, multimodal perception and environmental modeling are the focus of technology in recent years. "The biggest difficulty in human imitation lies in the imitation of the human brain, and the existing scientific theories are far from enough to study the human brain"; in terms of the "cerebellum", human-computer interaction capabilities, complex terrain passage, whole-body coordinated fine operations, etc. are important directions; in terms of the "body", key technologies such as rigid-flexible coupling bionic transmission mechanism, highly compact robot limb structure and dexterous hand design are important hardware foundations required for the flexible movement of humanoid robots.
The emergence of large models has significantly "evolved" the robot's "brain", greatly improved the versatility and generalization of robots, and is expected to reduce the development cost of humanoid robots and accelerate their entry into thousands of households.
According to Yang Fengyu, founder and CEO of Uniqi Robotics Technology Co., Ltd., the industry now mainly uses pre-trained large models to pre-train robots to give them stronger learning capabilities; large models can transfer the learning of specific tasks to robot tasks to improve their adaptability; in addition, the multimodal processing capabilities of large models can be used, combined with various inputs such as vision, hearing, and touch, to enhance the robot's understanding of complex scenes.