In the era of rapid technological advancement, humanoid robots, as a cutting-edge technology in the fields of artificial intelligence and automation, are gradually infiltrating our daily lives. From industrial manufacturing to medical rehabilitation, from service and entertainment to rescue and military operations, the application prospects of humanoid robots are increasingly broad. Behind all this lies the chip, a core component indispensable to their functionality.
1. The Importance of Chips in the Field of Humanoid Robots
Humanoid robots rely heavily on powerful chips to achieve various complex functions such as walking, grasping, and interacting. The chip serves as the "brain" of the robot, determining its performance, level of intelligence, and applicability in different scenarios. It processes data from various sensors, executes complex algorithms, performs real-time analysis and decision-making, and thereby controls the robot's movements and behaviors. It can be said that the chip is the key to the intelligence of humanoid robots.
2. Types of Chips Required for Humanoid Robots
① Motion Control Chips
Motion control chips are central to the agile movements of humanoid robots. They are primarily integrated into core components such as microcontrollers (MCUs), motor control chips, and field-programmable gate arrays (FPGAs)/application-specific integrated circuits (ASICs), working together to achieve precise control over the robot's movements.
· Microcontrollers (MCUs)
MCUs are one of the common chips in humanoid robots, integrating modules such as CPU, memory, and I/O interfaces. They are advantageous for their small size, low power consumption, and relatively low cost.
MCUs are mainly responsible for processing basic control logic and sensor signals, executing simple control algorithms. For example, they can receive data from sensors like accelerometers and gyroscopes, process it through built-in control algorithms, and then send control commands to motors and joints, directing the robot's actions.
· Motor Control Chips
Motor control chips serve as the "muscle controllers" of humanoid robots. They receive commands from MCUs and precisely control parameters such as motor current, voltage, and frequency, thereby achieving precise control over the robot's movement speed, strength, and position. Servo motors are key components for motion control in humanoid robots, with motor control chips being the core of the servo motor drive system.
For example, dedicated chips designed for brushless DC motors (BLDCs) and microstepping motors can efficiently control motors, offering high integration, low energy consumption, and precise adjustment of motor speed, direction, and torque.
· FPGAs/ASICs
FPGAs and ASICs are commonly used in humanoid robots with extremely high performance requirements. FPGAs offer high flexibility and reconfigurability, allowing programming and configuration according to specific application needs for high-speed signal processing and control. ASICs, on the other hand, are custom-made for specific applications, featuring high performance, low power consumption, and high integration.
In humanoid robots, FPGAs and ASICs can be used to implement complex motion control algorithms, image processing algorithms, etc., meeting the stringent requirements for real-time performance, accuracy, and efficiency.
② Perception System Chips
Perception system chips are crucial for humanoid robots to acquire information about the external environment. They are mainly integrated into sensor chips (including vision, auditory, tactile, etc.), embedded vision and AI processing chips, and communication chips in wireless communication modules, collectively constituting the robot's perception system.
· Sensor Chips
Sensor chips are essential tools for humanoid robots to perceive the world. They can real-time sense changes in the surrounding environment and the robot's own state, providing indispensable data support for decision-making.
For example, vision sensor chips can capture image and video information for tasks such as target detection, tracking, and recognition. Auditory sensor chips can capture sound signals for language recognition and interaction. Tactile sensor chips can perceive the pressure and distribution when the robot comes into contact with external objects, aiding in grasping operations.
· Embedded Vision and AI Processing Chips
Embedded vision and AI processing chips are core to the intelligent perception and decision-making of humanoid robots. They can process and analyze data collected by sensors in real time, such as target detection, tracking, and recognition, providing strong support for autonomous decision-making and planning of humanoid robots.
For example, some vision vendors integrate vision technology and AI processing units, enabling advanced processing and analysis of images and videos collected by vision sensors, enhancing the robot's visual perception capabilities.
· Communication Chips in Wireless Communication Modules
Communication chips in wireless communication modules are responsible for information transmission between the robot and the outside world. For example, they can receive control commands and upload perception data, ensuring real-time communication. In humanoid robots, wireless communication modules are key components for remote control and data exchange.
③ Decision and Planning System Chips
Decision and planning system chips are central to the intelligent decision-making and planning of humanoid robots. They process data from various sensors, execute complex algorithms and logical operations, perform real-time analysis and decision-making, and plan the optimal action paths and execution schemes.
· Main Control Chip/Central Processing Unit (CPU)
The main control chip/CPU serves as the command center of the humanoid robot, integrating high-performance computing units and complex algorithms. It can quickly process data from various sensors, execute complex logical operations and real-time analysis, thereby planning the best action paths and execution schemes. In humanoid robots, the performance of the CPU directly determines the robot's level of intelligence and decision-making capability.
· Graphics Processing Unit (GPU)
The GPU is the visual hub of the humanoid robot, specializing in efficient image processing and graphics rendering. It is crucial for visual recognition, face recognition, and interaction interfaces of humanoid robots.
For example, GPUs can accelerate the training and inference processes of neural networks, enhancing the robot's visual perception and decision-making capabilities.
· Dedicated Decision and Planning Chips
In certain high-end or specific application scenarios of humanoid robots, higher computational power is required. Thus, dedicated decision and planning chips have emerged.
For example, AI processor chips are specifically designed to accelerate the execution of AI algorithms such as machine learning and deep learning. Compared to traditional GPUs and CPUs, they offer significantly improved performance with extremely low power consumption, significantly enhancing the accuracy and efficiency of decision-making and planning.
④ Speech Recognition and Interaction Module Chips
These chips are key to enabling natural and fluent voice communication in humanoid robots. They are distributed across components such as microphone arrays, speech chips, and audio processing units, working together to equip the robot with functions such as speech recognition, speech synthesis, noise suppression, and speech enhancement.
Furthermore, they can enable more advanced interaction experiences such as situation recognition and generation, and offline voice interaction. The speech recognition and interaction module is closely connected to the robot's control system, responsible for remote control and data exchange, ultimately facilitating natural and fluent voice communication for humanoid robots.
3. How Humanoid Robot Chips Work
The operation of humanoid robot chips involves multiple complex and precise processes, primarily including data acquisition, data processing, decision-making and planning, and command transmission.
① Data Acquisition
Humanoid robots collect real-time information about their surrounding environment through various built-in sensors, such as visual, auditory, and tactile sensors. These sensors convert the collected data into electrical signals and transmit them to the chip. The chip receives these signals through interfaces, preparing for subsequent data processing.
② Data Processing
After receiving data from the sensors, the chip first performs preprocessing, such as filtering and amplification, to improve the accuracy and reliability of the data.
Then, the chip uses built-in algorithms and programs to conduct in-depth analysis and processing of the preprocessed data. These algorithms may include image recognition algorithms, speech recognition algorithms, motion control algorithms, etc. Through complex calculations and analyses, the chip can extract useful information, providing a basis for subsequent decision-making and planning.
③ Decision-Making and Planning
Based on the processed data, the chip makes decisions and plans according to preset goals and planning. For example, when the robot detects an obstacle ahead, the chip will decide to take actions such as bypassing or stopping. The decision-making and planning process involves complex logical operations and real-time analysis to ensure that the robot can make optimal decisions.
During the decision-making and planning process, the chip also needs to consider the robot's kinematics, dynamics, and other physical characteristics to ensure that the planned action paths and execution plans are feasible and efficient.
④ Command Transmission
Once a decision is made, the chip sends commands to the robot's actuators, such as motors or shutdown mechanisms.
These commands include the actions and parameters that the actuators need to execute, such as motor speed, direction, joint angles, etc. After receiving the commands, the actuators perform the corresponding actions, thereby achieving the robot's overall movement and task execution.
4. Technical Characteristics of Humanoid Robot Chips
The technical characteristics of chips determine the performance and intelligence level of robots.
① High-Performance Computing Capability
Robots have a large amount of data from sensors that needs to be processed and execute complex algorithms for decision-making and control.
Therefore, high-performance computing capability is one of the essential technical characteristics of chips. High-performance processors such as CPUs and GPUs provide powerful computing capabilities, enabling robots to complete various tasks quickly and accurately.
With the development of artificial intelligence technology, dedicated AI chips such as Neural Processing Units (NPUs) are gradually being applied to humanoid robots, further enhancing their intelligence level.
② High Precision and Low Power Consumption
Humanoid robots have extremely high requirements for precise motion control, so chips need to have the technical characteristics of high precision and low power consumption.
MCUs and motor control chips need to precisely control parameters such as motor current, voltage, and frequency to achieve precise control of the robot's movement speed, force, and position.
At the same time, to extend the robot's operating time, the chip also needs to have low power consumption characteristics. Some MCUs and sensor chips specifically designed for low power consumption are widely used in humanoid robots.
③ High Integration and Modular Design
High integration can reduce the size and power consumption of the chip, improving the reliability and stability of the system; modular design facilitates component replacement and simplifies the process of creating different controller combinations.
Chips such as FPGAs and ASICs have high flexibility and reconfigurability, allowing them to be programmed and configured according to specific application needs. At the same time, some chip manufacturers also provide a rich set of IP cores and development tools to support modular design applications.
④ Real-Time Performance and Stability
Robots have extremely high requirements for the real-time performance of their control systems, so chips need to have the technical characteristics of real-time performance and stability.
MCUs and motor control chips need to quickly respond to and process various commands and data to ensure the robot's motion performance. At the same time, they also need to have stable working performance and anti-interference ability to cope with complex and changing application environments.
Chips are an indispensable component in the development of robot technology. With the continuous advancement of technology, the performance and functionality of humanoid robot chips will continue to improve, injecting new vitality into the development of robot technology.
