Composition and operation method of mobile robot

Mobile Cognition

What parts does a mobile robot consist of? Let’s get to know it together.

Let's first look at a mobile robot that we will frequently mention in the following content - LIMO. LIMO comes from Songling Robotics and is the world's first development platform that integrates four motion modes. It can realize four-wheel differential, Ackerman, crawler, and Mecanum wheel motion modes, which can support our robot design to the greatest extent. LIMO uses Jetson Nano as the main control system and ROS as the core software environment. It supports a variety of applications such as SLAM, autonomous navigation, image recognition, etc., and is also equipped with a professional sandbox.

Next, we will use LIMO as an example platform to start the cognitive learning of mobile robots. This article is divided into two sections, which mainly lead you to understand the definition and composition structure of mobile robots, and take the LIMO robot as an example to introduce the operation method and motion mode of mobile robots, so as to help you establish an overall understanding of mobile robots.

1.2.1 Definition and composition of robots

Definition of Robot

○ Birth: In 1920, Czechoslovak writer Karel Capek created the word "robot" in his science fiction novel "Rossum's Universal Robots", based on Robota (Czech, originally meaning "labor, hard labor") and Robotnik (Polish, originally meaning "worker").

○ Baidu Encyclopedia: A robot is a machine device that performs work automatically. It can accept human commands, run pre-programmed programs, or act according to technical principles. Its mission is to assist or replace human work, such as manufacturing, construction, or dangerous work.

○ Robotics Association (RIA): A robot is a multifunctional manipulator used to carry materials, parts, and tools, or a special device that can complete various tasks through changeable programmed actions.

The four major components of a robot

From the control perspective, the robot can be divided into four major components as shown in the figure, namely: sensor system, actuator, drive system and.

Figure 2-3 Four major components of a robot

The four major components of the robot are interdependent and interconnected, forming a complete robot control loop.

Figure 2-4 Control circuit of the robot

If a robot is compared to a person, the actuators are the hands and feet of the human body, which complete the execution of specific actions and also establish relationships with the external environment.

The drive system is similar to the muscles and bones of the human body, providing the body with a constant supply of power.

The sensor system is the human body's senses and nerves, which collect internal and external information and feed it back to the brain for processing.

The control system is the brain, processing various tasks and information and issuing control commands.

As robot software changes with each passing day, these four major components are also constantly evolving and optimizing, jointly promoting the robot towards intelligence.

•Executive organs: the hands and feet of the human body, which complete the execution of specific actions.

•Drive system: The muscles and bones of the human body are the source of power for the movement of the entire body.

•Sensor system: The human body’s senses and nerves, which mainly complete input and feedback, including internal sensor systems and external sensor systems.

•Control system: The brain of the human body, which realizes the processing of tasks and information and outputs control command signals.

Next, let’s take the LIMO robot as an example to see how these four major components work together in such a typical mobile robot.

Figure 2-5 LIMO robot

Figure 2-5 shows the appearance of LIMO. At first glance, it looks like a beautifully designed car. Based on Jetson Nano, it is equipped with a variety of actuators and can perform multiple functions such as autonomous navigation, image recognition, and path tracking.

So what are the actuators of LIMO? Yes, they are the four actuators on the chassis and the four wheels connected to it.

LIMO uses a hub motor, that is, the stator and rotor of the motor are integrated inside the wheel, saving the space occupied by the motor in a general car, and the acceleration and deceleration control performance is also more outstanding.

Not only that, the chassis of LIMO is also equipped with a switch for a special transmission device. For example, we can use the four wheels to rotate independently to make the car move forward, backward and turn. If you want to simulate the Ackerman movement of a real car, just pull out the two red pins in front to achieve a similar Ackerman movement, and turn the car through the parallel steering of the front wheels. If you are outdoors, you can replace the tires with tracks to achieve better off-road performance. If you want the car to walk sideways like a crab, you can also use Mecanum wheels for omnidirectional movement. So on a LIMO car, we can dynamically switch between four movement modes, which are all achieved by relying on the special design of the car's own actuator.

Figure 2-6 Four motion modes

The drive system plays an important role in driving LIMO's four motion modes and the various sensors it is equipped with.

Figure 2-7 Drive system board

As shown in Figure 2-7, this driver board is installed in the chassis of LIMO, and is connected to various devices of the car through a variety of connections. This board is the core, which is what we often call or, and the driver we write runs in it, and then through a level of signal conversion, it connects with the outside world through connectors.

Odometer

In order to keep track of the car’s internal and external information, a sensor system is essential. Let’s first look at an internal sensor of a LIMO robot, which is also a sensor commonly used by mobile robots - the odometer.

Similar to a car meter that records mileage, the mileage can be recorded by the number of wheel rotations. Robots generally also have a sensor installed on the wheel or motor to detect the rotation speed of the wheel and integrate the time to obtain the robot's real-time position and speed. The device used for this function is called an odometer, and the device that implements this function is not the only one.

For example, on some small cars, you will see a code disk installed next to the motor with many slits on it. The rotation of the motor drives the code disk to rotate, and the light emitted by the tube will pass through the gaps at a certain frequency and be collected by the receiving end. Through this sampling frequency, we can calculate the rotation speed of the motor, and thus obtain the robot's own status information such as how far it has walked and how many degrees it has rotated.

LIMO uses another type of odometer, called a Hall sensor. As shown in Figure 2-8, this is a wheel hub motor with a motor coil inside. The green circuit board is a Hall sensor. When the motor rotates, the Hall sensor follows the movement and can measure the motor's rotation speed by sensing the signal generated by the surrounding magnetic field, thereby obtaining the robot's status information.

Figure 2-8 Hall sensor

Whether it is a photoelectric encoder or a Hall sensor, the number of wheel rotations is calculated based on the number of pulses generated in the sampling unit time, and the robot's movement speed is calculated by the circumference of the wheel. After integrating the speed over time, the mileage information is obtained. This is the basic principle of the odometer.

However, the odometer also has a problem, that is, there will be errors in each measurement. After continuous integration, the error will inevitably be amplified, which is what we often call the odometer cumulative error. We will introduce the solution to this problem in the subsequent content.

Robot odometer distance measurement principle:

• Calculate the number of revolutions of the motor/wheel based on the number of pulses generated per unit time

• Calculate the robot's speed based on the circumference of the wheels

• Calculate mileage based on the robot's speed integral

External Sensors

Now that we have the robot's own status information, how do we obtain information about the external environment? LIMO is equipped with two important external sensors.

One is a 3D camera, which is similar to the human eye. The 3D camera can not only see the color information of the external environment, but also obtain the depth information of each obstacle from itself. The principle is different from the binocular positioning of the human eye. The 3D camera has three "eyes". One of the "eyes" is an ordinary camera, which is used to obtain the color information of an image. The other two eyes, one is responsible for emitting light, not a point, but a surface, and the other is responsible for receiving the reflected infrared light. This back and forth, we get a depth image. With the color image and the depth image, we overlap the two images together to know the color and depth information of each pixel. This is the registration process. Through this series of complex collection and registration processes, we finally get the complete environment information, which we call a 3D point cloud. Each point is composed of RGB color values ​​and XYZ coordinate values. Future 3D mapping and object recognition all rely on this information.

Figure 2-9 3D camera

Although 3D cameras are rich in information, their detection angle and accuracy are limited, so mobile robots are generally equipped with a laser radar. The principle of laser radar is relatively simple. A laser head emits laser, and another receiving head receives the reflected light. Then the distance can be measured by the flight time of light, as shown in Figure 2-10. There is also a motor here to drive the transmitting and receiving heads to rotate at a constant speed. By rotating and detecting at the same time, the distance of many points within a 360-degree range can be obtained. In this way, we can obtain the depth information of obstacles in the plane where the radar is located. The future SLAM map construction and autonomous navigation are all based on this data.