Mounting the Camera and Powering the Vision Kit

Vision Kit Contents:

• Vision kit computer and power supply
• Ethernet splitter (1-to-2) (optional)
• 3D camera and mounting plate
• USB cable and cable guides

Instructions:

1. Attach the Camera
   Mount the camera and its plate onto the robot. Align the two holes on the mounting plate with the holes on the robot’s 5th axis body and secure them. Make sure the camera plate is not tilted and straight.

2. Connect the USB Cable to the Robot
   Plug the USB cable into the robot's USB port. Ensure the screws on the USB connector are securely fastened to prevent loose connections.

3. Connect the USB Cable to the Vision Kit
   Pass the USB cable to the vision kit and insert it into one of the blue USB 3.0 ports (blue USB ports).

4. Organize the USB Cable
   Use the cable guides to route the USB cable neatly. Ensure the cable does not obstruct the robot’s movement or become tangled.

5. (Optional) Set Up the Ethernet Splitter

   • To minimize the number of Ethernet cables running between devices, use the Ethernet splitter.
   • Place the robot controller, vision kit, and splitter close together for easy connection.
   • Connect the robot controller and vision kit to the splitter using the provided short Ethernet cables. Plug these cables into the two Ethernet ports on the splitter (the side with two ports).
   • Connect an Ethernet cable from the single-port side of the splitter to your computer or router.
   • Power the splitter by connecting its USB cable to one of the gray USB 2.0 ports on the vision kit.

6. Power the Vision Kit
   Connect the USB-C power supply cable to the vision kit and plug the other end into a wall outlet.

🚨 Notice: Ensure all connections, including the camera and cables, are properly set up before turning on the vision kit.

Connect to the Vision Kit

The vision kit is equipped with a single-board computer running a 64-bit Debian-based Linux distribution to execute your vision applications. The default hostname, username, and password for the vision kit are as follows:

# hostname
vision

# username
dorna

# password
dorna

IP Address

If the vision kit is connected to a router with a DHCP server, the IP address will be automatically assigned. If it is connected directly to your computer via the Ethernet port, you will need to manually configure the IP address.

1. SSH into the Vision Kit
   Open a terminal and use the following command to SSH into the vision kit (log in with the password dorna):

   ssh dorna@vision.local

2. Open the Network Configuration Tool
   Type the following command to open the network configuration interface:

   sudo nmtui

3. Edit the Connection

   • Select Edit a connection.
   • Choose the relevant connection type (e.g., Wired connection 1).

4. Configure the IPv4 Settings

   • Set IPv4 CONFIGURATION to Manual.
   • Enter the following details:
     • Address: Assign a static IP address to the vision kit (e.g., 192.168.1.100).
     • Gateway: Enter the gateway address (typically your router's IP address, e.g., 192.168.1.1).
     • DNS: Use a DNS server address, such as 8.8.8.8 (Google's public DNS).

5. Save the Configuration

   • Click OK to save your settings.
   • Press and then to exit the configuration tool.

6. Reboot the Vision Kit
   Type sudo reboot to reboot the vision kit and apply the changes.

🚨 Note: If the vision kit is connected to a router with a DHCP server, the IP address will be assigned automatically by the router.

Accessing Dorna Lab

To access the Dorna Lab software, enter the vision kit's IP address in your web browser by typing http://robot_ip_address.
To connect to a robot from the Dorna Lab session, follow these steps:

1. Click on Settings in the top navbar.
2. Go to General Info.
3. Under Robot System IP, enter the robot's IP address.
4. Click Set.

Detection App and API

The vision kit includes a detection app that allows you to visually build your vision applications directly from a web browser.

To access the detection app, navigate to:

http://robot_ip_address:8888/doc/workspaces/auto-g/tree/Downloads/vision/example/detection_app.ipynb

Alternatively, you can open a new Python3 kernel in Jupyter Notebook and run the following code:

%matplotlib widget
from dorna_vision import Detection_app
x = Detection_app()

The detection app automatically generates the necessary API calls for you. You can then use these generated calls within your code to perform object detection, simplifying the process and integrating detection capabilities seamlessly into your applications.

Upgrade the Software

To upgrade the vision kit software, SSH into the vision kit and run the following command:

sudo mkdir -p /home/dorna/Downloads && sudo rm -rf /home/dorna/Downloads/upgrade && sudo mkdir /home/dorna/Downloads/upgrade && sudo git clone -b vision https://github.com/dorna-robotics/upgrade.git /home/dorna/Downloads/upgrade && cd /home/dorna/Downloads/upgrade && sudo sh setup.sh dorna_ta

Troubleshooting and Resolving Common Issues

1. Running Multiple Detection Sessions

You cannot run multiple sessions of the detection app at the same time. If you are done with a detection session and need to start a new one, you should kill the existing kernel in Jupyter Notebook. To do this:

• Go to the Jupyter Notebook interface.
• In the "Running" tab, you will see a list of active notebooks.
• Find the notebook running the detection app.
• Click the "Shutdown" button next to the notebook to kill the kernel and stop the session.

This will free up resources for a new session.

2. Camera Not Responsive

If the camera is not responsive, follow these steps:

• Disconnect and reconnect the USB cable from the vision kit side.
• After reconnecting, kill the Jupyter session running the program by following the steps above.
• Re-run the program by restarting the Jupyter notebook.

This should resolve any camera connectivity issues and allow the detection app to function properly again.