What Type Of IC Is Used In An AI Robot?

What type of IC is used in an AI robot?

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The artificial intelligence robot is becoming a new norm in robotics. This is mainly due to the fact that most modern robots are powered by AI and machine learning. These new robots have the capabilities to think and act like humans. At the center of all these developments are integrated circuits (ICs). An IC comprises a set of integrated circuits that are designed to execute different functions in a system.

IC chips have been part of robotics for years. Even as modern robots have shifted to AI, they are still used. The only difference is these chips are more oriented toward the implementation of artificial intelligence in robots. In this article, we are going to discuss the specific IC chips that are used in AI robots.

Components of AI robots

In order to know the types of semiconductor chips that are used in AI robots, it will be vital to have an overview of the key components that make up an AI robot. After all, the ICs are used for executing tasks on different parts of a robot. The main components include:

  • Power supply unit: This component of an AI robot is responsible for all the functions that are related to the supply and distribution of power in a system. It ensures that the right amount of current or voltage is allowed into a robot from the external outlet. The power supply unit is also responsible for converting electricity from AC to DC
  • Actuator: Actuators in robotics are mainly used for converting electrical energy into mechanical energy. They are responsible for executing different types of movements on a robot.
  • Electric motors: The working mechanism of a robot is heavily characterized by rotational movement. This is possible thanks to the presence of electric motors.
  • Pneumatic muscles: Just like humans, robots have muscles that are referred to as pneumatic air muscles. They contract and relax when doing different types of tasks.
  • Muscle wires:  These are wires that are responsible for the transmission of electric signals. The signals can be from sensors to the robot’s central processing unit or the other way around.
  • Sensors: Like human beings, sensors are the data collectors on an AI robot. They perceive the conditions in an environment so that the robot can execute necessary actions.  Data collection by sensors is done in real time.
  • Memory components: Robots have a memory device that stores all the instructions about the operation and functions of the robot.  The fact that our focus is on AI robots means that the memory component has vital information about its intelligent learning models.
  • User interface: Despite the fact that AI robots have high levels of independence, they also rely on some human control.  They have a human-friendly user interface that allows human controllers to exert some level of control over the system.

Types of IC chips used in AI robots

Now that you know the different components of AI robots, let’s look at the specific integrated circuits that are used in these robots and what they do.

Central processing unit chips

Just like in normal computers, CPUs are chips designed to perform the general data processing tasks in AI robots. They serve as the brains of robots in that they coordinate all robotic system operations.

Sensors in robots send signals to the CPU chip for processing and execution of tasks. The central processing unit coordinates muscle movements on robots. The machine learning algorithms are processed and executed by the central processing unit component of a robot.

Application-specific integrated circuits (ASICs)

ASICs are heavily featured in the world of robotics. As the name suggests, they are designed for performing specific tasks and roles in applications. In the case of AI robots, these chips perform roles that are mainly related to artificial intelligence and machine learning.

The fact that ASICs are tailored for specific roles means that they have what it takes to deliver the best performance whenever they are integrated into the robots. For example, they can process and execute data that is geared toward a specific goal.

A perfect example of ASIC in AI robots is the Tensor Processing Unit from Google. It is specifically designed for the training and execution of machine learning algorithms.

Graphics Processing Unit

Graphics is an important aspect of artificial intelligence and machine learning. It is mainly used for training AI models.  Unlike general-purpose chips, GPUs are tailored for processing data that is in the graphics form.

AI robots rely on the graphics chips for processing complex computations that are related to graphics. For example, an AI robot will analyze the physical components of its environment before it performs any task. This should happen in real time.  Such complex data processing tasks can only be done with the help of the graphics processing unit.

Vision processing unit

Closely related to the GPU is the vision processing unit (VPU). These chips are specifically dedicated to processing visual data. It gives an AI robot the power and capability to perceive physical objects when moving around or even executing different tasks.

An AI robot is capable of differentiating the faces of people or colors of objects thanks to the vision IC.  This chip is usually integrated into cameras that are installed on AI robots. The camera will serve as a data collector and the VPU will process and execute this data in real-time.

Neural Processing Unit

It is impossible to separate AI and neural networks. While the basic chips can perform neural network operations, there is always a need to get better performance from a processor. This is where neural processing IC comes in.

Neural processing units are suitable for AI-related tasks such as speech and image recognition. They process and execute audio commands faster and in real-time.  Neural processing units are also highly credited for their accuracy and efficiency when it comes to the execution of complex AI algorithms.

Network ICs

In most applications, AI robots are connected to other devices in a network. Smooth reliable network connections are possible thanks to the power of dedicated network ICs. These are types of ASICs that are specifically designed for network communication.

The growing popularity of the Internet of Things (IoT) makes it more important for AI robots to have network-integrated circuits. It makes it possible for the robots to be controlled from remote locations.

Security ICs

Security is an important topic in the world of robotics, especially when we consider the fact that these are AI robots and can be operated remotely. Dedicated ICs are used for implementing physical security as well as network security.

In relation to physical security, security ICs are used for controlling access to the robot. They are embedded with authentication programs such as passwords and facial recognition technology. For network security, there are specific ICs that protect the robot from remote attacks by hackers.

Power IC

AI robots fully rely on electric energy to perform different tasks. They have power ICs that control all the activities that are related to the power usage in a system. Power units in AI robots have power ICs that control the intake of power from the source.

Power ICs are also responsible for the distribution of power to different components of a robot. Through AI and machine learning, power chips facilitate smart distribution and consumption of energy by the AI robots. Using special algorithms, the chips are able to maximize and minimize energy consumption in robots. The overall result is a high energy efficiency rating of an AI robot.

Properties of chips for AI robots

We have just looked at different integrated circuits that are used in AI robots. What makes a particular chip suitable for such a robot? What features should the chip have? Here are some of the basic properties of ICs that are used for robotics:

  • Fast processing speed: All the actions performed by robots are in real-time. It will be necessary for the chip to support the needs for these speeds. The high speeds of these chips are supported by parallel processing technology on ICs.
  • Specialization: The chips will be effective only if they are customized for specific AI tasks.
  • Reliability: The ICs should perform their functions accurately and efficiently without fail.
  • Scalable: Most AI applications are characterized by the unprecedented demand for data. The chips should be capable of supporting such demands without causing the system to fail.
  • High data capacity: Since AI is a data-driven technology, the ICs should be capable of handling large chunks of data.


In as much as AI robots are designed to perform high-level functions, there are any basic operations that support the high-level operations. The execution of these operations is mainly done by the microcontroller. Some of these low-level operations include the rotation of motors, physical integration with other devices, and thermal management among others.


Are you building an AI robot? It is important to know the types of integrated circuits that are used in robotics. With this information, you will be in a perfect position to make an informed decision when it comes to buying ICs for AI robots.

Last Updated on October 30, 2023 by Kevin Chen

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