Programme and teach Jetracer using Matlab and Simulink
Understand the Libraries used in JupytrLab
Working on previous Task
10
04.09.2024
Discussion of subject for the bachelorthesis.
Drive the JetRacer in the right lane counterclockwise with the gamepad controller. Limit the speed via Software to a maximum (e. g. 1 m/s).
Take a video while driving a lap with MATLAB® using a MATLAB®-script.
Load the pretrained NN.
Train the pretrained NN with MATLAB® with a MATLAB®-App (GUI) by clicking the desired path in the images.
Use classic lane tracking algorithms to teach the NN automatically.
Write a PD-contoller that uses the NN to drive in the right lane. Program this in MATLAB® and let it run on the JetRacer-GPU using GPU Coder.
Goal: the car should drive autonomously several laps in the right lane as fast as possible.
Student choosed a name fot the bachelorthesis.
Provide debug option to adjust speed(Throttle) of jetracer to a maximum (e. g. 1 m/s) only on matlab.
11
09.09.2024 - 13.09.2024
Student did not attend the meeting.
Please cancle the meeting if you are not coming.
Drive the JetRacer in the right lane counterclockwise with the gamepad controller. Limit the speed via Software to a maximum (e. g. 1 m/s) wit Professor's assistance.
Take a video while driving a lap with MATLAB® using a MATLAB®-script.
Load the pretrained NN.
Successfully Drive the JetRacer in the right lane counterclockwise with the gamepad controller on matlab. Hard code the speed Limit via Software to a maximum (e. g. 1 m/s).
Successfully took a video while driving a lap with MATLAB® using a MATLAB®-script.
Load the pretrained NN.
Attempt to train the pretrained NN with MATLAB® with a MATLAB®-App (GUI) by clicking the desired path in the images.
Documented all my work on wiki platform
12
16.09.2024 - 20.09.2024
Use classic lane tracking algorithms to teach the NN automatically.
Write a PD-contoller that uses the NN to drive in the right lane. Program this in MATLAB® and let it run on the JetRacer-GPU using GPU Coder.
Goal: the car should drive autonomously several laps in the right lane as fast as possible.
Send professor recorded video online
13
21.09.2024
Student did not appear to the weekly appointment.
Further research on how to train jetracer
Feedback from professor to use hshl gpt for advance research on how to train a NN
13
30.09.2024
Asking hshl gpt on how to train a NN with the video input from jetracer
Training jetracer based on the researches
Uning alternative method(using gamepad to train the jetracer frame by frame with linear image processing method)
13
07.1.2024
Show professor my work progress on NN traning and
Testing the jetracer steering and develop PID control
13
14.10.2024
Testing jetracer to complete a complete lap on the right lane
Recieved feedback from professor to train jetracer to get both input from controller and camera
Training the jetracer to get both input from controller and camera
Documenting all work progress
Errors and Solutions
#
Dates
Error Descriptions
Solutions
1
12.06.2024- 05.07.2024
Build the Jetracer
Setup Integrated Nvidia OS
Connect JetRacer to local WLAN
Setup Headless control of jetracer
Teach the JetRacer automated driving
Steering JetRacer with Gamepad
Teaching Jetracer interactive_regression
Testing different Flashversions of the JetRacer
Dokumentieren Sie bitte hier Ihren Fortschritt.
* jetbot-043_nano-4gb-jp45.zip
Warning!! this is for Jetbot, not Jetracer.
Jetracer cannot detect SD-card
Connot lunch Nvidia OS because HMI Screen always dark and Jetson Nano turns on but doesn’t boot
Incompatible with Jetracer and gives error :ValueError: No I2C device at address: 0x60 (error comes from step 5 of https://www.waveshare.com/wiki/JetRacer_AI_Kit. do not immplement it for pro versions )
only interactive_regression package works with no error
- **Edit `.bashrc`:**
Since `vim` and `nano` are unavailable, use `vi` if it's installed:
``Code:
vi ~/.bashrc
```
- **Clean Up Environment Variables:**
Update the `.bashrc` file to remove duplicates and ensure only one set of `PATH` and `LD_LIBRARY_PATH` entries:
```Code:
# Add CUDA bin & library paths
export PATH=/usr/local/cuda-10.2/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-10.2/lib64:$LD_LIBRARY_PATH
```
- **Save and Exit:**
- In `vi`, press `i` to enter insert mode.
- Make your changes.
- Press `Esc`, then type `:wq` and press `Enter` to save and exit.
- **Source `.bashrc`:**
Code:
source ~/.bashrc
Install Cudnn
Dokumentieren Sie bitte hier Ihren Fortschritt.
SDL 1.2 installation
1. **`nvcc`**: Ensure CUDA is correctly installed and its path is added to your `.bashrc` file.
2. **SDL 1.2**: Install the development libraries for SDL 1.2 on your system. You can typically do this with:
```code:
sudo apt-get install libsdl1.2-dev
```
No publick key(update error)
The following signatures couldn't be verified because the public key is not available: NO_PUBKEY A4B469963BF863CC
Reading package lists... Done
W: GPG error: http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 InRelease: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY A4B469963BF863CC
E: The repository 'http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 InRelease' is not signed.
N: Updating from such a repository can't be done securely, and is therefore disabled by default.
N: See apt-secure(8) manpage for repository creation and user configuration details.
The error message indicates that the GPG key for the NVIDIA CUDA repository is missing. To resolve this, you can manually add the key:
.png)