In recent years, the increasing global labor shortage and rising labor costs have led to a growing focus on humanoid robots in the international market. Governments and businesses worldwide have been increasing their investments to drive the development and application of robot technologies. According to research by TrendForce, China, Japan, the United States, South Korea, and Germany have long been the top five countries in terms of industrial robot installations. By 2025, these countries are expected to invest over US$13 billion in related fields. Against this backdrop, humanoid robots, as a cutting-edge area of robot technology, are driven not only by market demand but also by breakthroughs in core chip technologies.
Market Segmentation of Humanoid Robots
The application scenarios of humanoid robots are expanding gradually, from industrial manufacturing to domestic services, healthcare, and entertainment. The market demand for these robots is becoming increasingly diversified. The United States, with its comprehensive AI ecosystem, is leading in the intelligent development of humanoid robots. In contrast, China is focusing more on supply chain integration and cost control, with the potential to introduce more affordable products in the future. This market segmentation is creating a tiered structure in the pricing and application levels of humanoid robots. High-end products are specialized for complex tasks and high-precision operations, while mid- and low-end products are more oriented towards everyday applications.
Chip Technology: The “Brain” and “Nervous System” of Humanoid Robots
Humanoid robots rely on four key types of chips to achieve complex movements and intelligent interactions: the main control chip, sensor chips, motor drive chips, and communication chips. These chips together form the “brain” and “nervous system” of humanoid robots, determining the upper limit of their performance.
The main control chip, as the core computing unit of humanoid robots, is responsible for processing sensor data, executing algorithms, and controlling the robot’s behavior. With the advancement of AI technology, main control chips need to have powerful computing power and efficient energy consumption ratios. Currently, GPUs and TPUs (Tensor Processing Units) dominate this field, but ASICs (Application-Specific Integrated Circuits) designed specifically for humanoid robots are emerging to meet the needs of specific tasks. For example, Tesla’s Dojo project uses its self-developed D1 chip, which is designed for AI training and can support complex algorithm processing for humanoid robots.
Sensor chips are crucial for humanoid robots to perceive the external environment. The precision and response speed of chips such as visual sensors, force sensors, and Inertial Measurement Units (IMUs) directly affect the robot’s movement coordination and environmental adaptability. In recent years, advancements in 3D visual sensors and tactile sensors have enabled humanoid robots to perform better in complex environments. By integrating various sensors and leveraging the processing power of AI chips, humanoid robots can achieve precise visual recognition and behavior prediction.
Motor drive chips are responsible for controlling the robot’s joint movements and are the foundation for performing complex actions. High-performance motor drive chips need to have high precision, low latency, and high reliability. With the increasing popularity of brushless DC motors (BLDC) and stepper motors, the design of motor drive chips is continuously being optimized to meet the flexibility and stability requirements of humanoid robots. For example, TI’s LMG2100R026 device integrates a half-bridge FET and driver, can handle a continuous current of 55A, and enhances operational reliability and stability through integrated protection functions.
Communication chips serve as the bridge for robots to communicate with the outside world, enabling data transmission between robots and the cloud or other devices. Whether it is the transmission of remote control commands or the uploading of data collected by robots, communication chips play a vital role. For example, the HPM6E00 series of chips integrates EtherCAT interfaces and TSN (Time-Sensitive Networking) support, enabling millisecond-level transmission of sensor data and precise time synchronization. With the rapid development of 5G technology, communication chips are evolving towards higher speeds and lower latency, providing strong support for real-time interaction and remote collaboration of humanoid robots.
Future Trends
As chip technology continues to advance, the performance of humanoid robots is expected to make a qualitative leap. Several key trends are likely to emerge in the coming years:
Firstly, the widespread adoption of specialized chips will become the norm. AI acceleration chips and motion control chips, designed specifically for humanoid robots, will gradually replace general-purpose chips. These specialized chips can offer higher energy efficiency ratios and significantly reduce costs, thereby promoting the large-scale commercial application of humanoid robots.
Secondly, the integration of edge computing and cloud computing will become a key direction for technological development. Future main control chips will place greater emphasis on edge computing capabilities, enabling humanoid robots to process most data locally and reduce dependence on the cloud. At the same time, by combining with cloud computing, robots can achieve more advanced collaborative learning and task allocation, further enhancing their intelligence levels.
Moreover, multimodal perception and fusion technology will be widely applied. As sensor chips continue to develop, humanoid robots will be able to process multiple types of information, such as visual, auditory, and tactile inputs, simultaneously. This will enable them to better understand and adapt to complex environments.
Lastly, low-power and high-reliability design will become important considerations in chip design. With the expansion of humanoid robots’ applications in domestic and medical fields, higher demands are placed on the power consumption and reliability of chips. The application of new materials and packaging technologies will further enhance chip performance and durability, ensuring the stability and safety of robots during long-term operation. These trends collectively drive the rapid development of humanoid robot technology, laying a solid foundation for their application in more fields.
Conclusion
The development of humanoid robots is inseparable from the support of chip technology, and innovations in chip technology will open up broader application scenarios for humanoid robots. In the future, with the widespread adoption of specialized chips, the rise of edge computing, and the maturation of multimodal perception technology, humanoid robots will not only shine in the industrial field but also penetrate deeply into daily life, becoming a capable assistant to human society. In this process, the progress of chip technology will undoubtedly be the core driving force behind the evolution of humanoid robots.
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