Composition and operation method of mobile robot

Figure 2-10 LiDAR

The drive system and sensor system we have seen above will eventually be connected to the control system, which is the Jetson Nano control board. The core of this board integrates a quad-core, which can meet the operation of some basic software, and a 128-core, which is also capable of basic image processing. For easy operation, there is also a touch screen at the back of LIMO, so we can control the robot even without a laptop.

Figure 2-11 Jetson Nano control board

From the screen, we can see that the main control board is running the Ubuntu system with LIMO as the core. In the future, any robot applications we need to develop will be launched based on this system as the platform. This is also the core of our subsequent operations. The subsequent content will focus on explaining it. Here, everyone just needs to clarify what the four major components of the LIMO robot are.

We will use Figure 2-13 to clarify the connection between the control board and external devices in the LIMO robot.

Figure 2-13 Connection between control board and external devices

As the core of the drive system, the motion controller is responsible for controlling the motor and servo. The motor drives the car to move, and the servo drives the front wheel steering in Ackerman mode. In addition, it is also necessary to connect the internal sensor odometer and IMU to complete the detection of the robot's own status.

The robot control system is the brain of LIMO. After running, we will learn functions such as autonomous navigation, map building, image recognition, etc. It will also have a small number of sensor-driven tasks by collecting information from external cameras and radars. The communication connection between this control system brain and the motion controller is completed through the serial port.

In order to facilitate the control of the robot, in the future we will use our own laptops to connect to the robot for coding and control.

In this large framework, the application functions in the dotted box are developed and implemented based on the ROS environment, and the functions in the motion controller are implemented based on . From this picture, you can also better understand the relationship between ROS development and development. The two have their own responsibilities, one is biased towards upper-level applications, and the other is biased towards low-level control, and together they realize the intelligent functions of the robot.

1.2.2 Mobile robot operation method

System Startup

Above, we have analyzed the equipment and principles of the four major components of the robot when it is static. Next, let's make the robot move and learn about the movement mode and sensor data of the mobile robot.

First we need to start the LIMO robot. Press the button on one side of the robot to start the process. After a while, you can see the green light around the switch is on, which means it is starting. When the screen on the back of the robot displays the desktop environment, it means the startup is successful.

Long press the switch to start the robot

Power on successfully, the switch lights up green

The startup is successful and the screen displays the desktop

Please pay attention to the power indicator light during use. When the battery is low, the indicator light will flash red and a buzzer alarm will sound, indicating that charging is required.

The battery is too low, the red indicator light flashes, please charge it in time

Next, we open the LIMO robot App, scan and connect to the corresponding one.

Next, you can use the mobile phone App to control the movement of the robot. The left joystick can control LIMO to move forward and backward, and the right joystick is used to control LIMO to turn left and right. The middle progress bar displays the current real-time speed.

If we switch the robot's motion mode, we also need to select the corresponding control method above in the mobile app, such as Ackerman motion, four-wheel differential motion, and Mecanum omnidirectional motion.

•kerMann: You need to manually switch the LIMO car to Ackerman mode, which is mainly used to calibrate the zero point, control forward and backward movement, and rotation angle;

•Mailun: You need to manually switch the LIMO car to Mailun mode, which mainly controls forward and backward movement, direction change and rotation on the spot.

Remote Control Sports

Next, let's try differential motion. Make sure the pins at both ends of the robot are inserted, the wheels are ordinary rubber tires, and the front lights are orange. Then select differential mode on the mobile app, and then you can control the robot's movement through two analog joysticks. The left one controls forward and backward, and the right one controls left and right turns. It's no problem to turn in a circle.

In addition to the four-wheel differential, the track differential can also be used in some scenarios where higher obstacle crossing capabilities are required.

At this time, keep the pins at both ends of the robot in the inserted state, install the attached track accessories on the outside of the ordinary wheels, and the front lights are still displayed in orange. The settings of the mobile app are the same as those of the four-wheel differential movement. Select the differential mode, the left joystick controls forward and backward, and the right joystick controls differential steering.

The cars we often see on the road use the Ackerman motion mode, which achieves turning by parallel steering of the two front wheels. This can also be achieved on the LIMO robot. In this mode, ordinary rubber wheels are still used, but the pins at both ends of the robot need to be pulled up. Note that after pulling them up, they need to be rotated and locked. The front lights will turn green, as shown in Figure 2-21.

Switch to Ackerman mode in the mobile phone APP. The left joystick is still used to control forward and backward movement. Try to move the right joystick. You can clearly see that the two front wheels of the robot will rotate parallel to the left or right around the axis. At the same time, controlling the left joystick can achieve turning movement.

The above three motion modes can only allow the robot to have a forward linear speed. If you want to achieve an effect similar to walking sideways like a crab, you need to switch to the omnidirectional motion mode.

We replaced the robot's four wheels with Mecanum wheels, and made sure to restore the pins at both ends of the robot to the unplugged state. The front light is blue. Select Mecanum wheel mode on the mobile app, and the left joystick can be shaken left and right. You can see that the robot has a lateral movement effect. If you want to control the robot's differential steering, continue to use the right joystick to turn left and right. The movement principle at this time is the same as the four-wheel differential.

Sensor data

Next, let’s take a look at the sensor data of the mobile robot.

First, we need to start the ROS visualization of the LIMO robot. You will soon see that the car has appeared in the interface. At the same time, we can also see the camera color information and 3D point cloud information of the car. You can drag it with the mouse to experience the effect of this 3D data.

Figure 2-23 Sensor data

The green dots that keep jumping around are the distances of obstacles seen by the laser radar. When the robot moves, these dots will continuously reflect the distance information of obstacles. At the same time, we can also see that if the robot moves, the coordinate system representing the robot's position in the host computer will also be updated and move. This is the position calculated by the robot's odometer. For example, if the odometer finds that the robot has walked 1m, the coordinate system will also move 1m.

Such a visual host computer is an important function in ROS. It not only allows us to intuitively see various information about the robot, but also makes it easier for us to debug the robot functions in the future.

Review editor: Liu Qing