Diskussion:JetRacer: Spurführung mit künstlicher Intelligenz: Unterschied zwischen den Versionen

Aus HSHL Mechatronik
Zur Navigation springen Zur Suche springen
Keine Bearbeitungszusammenfassung
Keine Bearbeitungszusammenfassung
Zeile 60: Zeile 60:
|-
|-
| 7  || 12.08.2024 ||
| 7  || 12.08.2024 ||
* Easy start without ROS: Run Image detection on GPU
* Easy start without ROS: Run Image detection on GPU with Professor's assistance
*[https://de.mathworks.com/videos/deploying-a-deep-learning-network-on-nvidia-jetson-using-gpu-coder-1506357891312.html Deploying a Deep Learning Network on NVIDIA Jetson Using GPU Coder]
*[https://de.mathworks.com/videos/deploying-a-deep-learning-network-on-nvidia-jetson-using-gpu-coder-1506357891312.html Deploying a Deep Learning Network on NVIDIA Jetson Using GPU Coder]
* [https://de.mathworks.com/matlabcentral/fileexchange/64534-getting-started-with-matlab-simulink-and-ros?s_tid=ta_fx_results Getting Started with MATLAB, Simulink, and ROS]
* [https://de.mathworks.com/matlabcentral/fileexchange/64534-getting-started-with-matlab-simulink-and-ros?s_tid=ta_fx_results Getting Started with MATLAB, Simulink, and ROS]
Zeile 93: Zeile 93:
* Student did not attend the meeting.
* Student did not attend the meeting.
* Please cancle the meeting if you are not coming.
* 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).
* 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.
* Take a video while driving a lap with MATLAB® using a MATLAB®-script.
* Load the pretrained NN.
* Load the pretrained NN.

Version vom 11. September 2024, 15:15 Uhr

# Termin Planung für die Woche Fortschritt
1 12.06.2024- 19.06.2024
  • Safety briefing for Marc Ebmeyer's laboratories
  • Familiarization with the existing frame work
  • Familiarize with the existing system using the wiki article. Gantt chart
  • Handing over the keys to Marc Ebmeyer's laboratories
  • Make Research on the topic
  • Draft a timeline for the project.
2 20.06.2024-26.06.2024
  • Build the Jetracer
  • Setup and Flash Nvidia OS
  • Connect JetRacer to local WLAN
  • Setup Headless control of jetracer
  • Errors and Crashes on the OS (details on Errors and solutions)
  • Find the optimal OS for the jet racer
  • Optimization of the AI for the circuit, the controller (e.g. PD controller) in the laboratory Autonomous systems (speed, robustness).
3 26.06.2024 - 05.07.2024
  • Fixing, debuging errors and testing different Flashversions of the JetRacer
  • Teach the JetRacer automated driving
  • Steering JetRacer with Gamepad
  • Teaching Jetracer interactive_regression
  • Make Research on Matlab, Deep learning and ROS
  • Document Errors
4 05.07.2024 - 26.07.2024
  • Link Jetracer to MATLAB
  • Install and check prerequisite for the jetracer like: CUDA, Cudnn, TensorRT
  • Reinstall CUDA 10.2, CuDNN and SDL1.2 Paths
  • Attempt to programme Jetracer using MATLAB:
  1. Image recognition
  2. Line following


  • Document Errors + Solutions (E.g. Incompatible GPU, Missing Environment Variables paths like: CUDA_PATH and NVIDIA_CUDNN)
  • Speak with other student working on Autonome Spurführung mit einem JetRacer ROS AI Robot
  • Update the Professor by Email for Feedback
6 29.07.2024 -
  • Programme Jetracer using ROS2
  • Evaluation of the advantages and disadvantages of the programming environments.
  • Successfully install and run ROS on jetracer
  • Recreate Alexnet Example on ROS image classification with GPU coder
7 12.08.2024
8 19.08.2024
  • Use the Game controller to steer

Dokumentieren Sie bitte hier Ihren Fortschritt.

9 26.08.2024
  • 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.

Dokumentieren Sie bitte hier Ihren Fortschritt.

|}

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


  1. Warning!! this is for Jetbot, not Jetracer.
  2. Jetracer cannot detect SD-card
  3. Connot lunch Nvidia OS because HMI Screen always dark and Jetson Nano turns on but doesn’t boot


Dokumentieren Sie bitte hier Ihren Fortschritt.

* jetson-nano-jp461-sd-card-image.zip(Jetson-nano developer kit)
  1. No build in Jetracer packages like: basic_motion, teleoperation, road_following etc
  2. Incompatible with Jetracer and gives error : jetson nano Adafruit-Blinka requires Python '>=3.7.0' but the running Python is 3.6.9
  3. Incompatible with Jetracer and gives error :No matching distribution found for Adafruit-Blinka>=7.0.0 (from adafruit-circuitpython-servokit)
  4. Cannot run "sudo nvpmodel -m1" and shows nvpmodel not found ||


* jetcard_nano-4gb-jp451.zip (Jetpack4.5.1)
  1. Working but no build in Jetracer packages like: teleoperation, road_following etc
  2. Solution is to use github repository: https://github.com/NVIDIA-AI-IOT/jetracer to clone the teleoperation, road_following etc
Dokumentieren Sie bitte hier Ihren Fortschritt.


* jetrace.zip (Jetpack4.5)
  1. 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 )
  2. only interactive_regression package works with no error
  3. Solution is to use github repository: https://github.com/NVIDIA-AI-IOT/jetracer to clone the basic_movement, teleoperation, road_following etc
  4. Can't connect to SSH header
Dokumentieren Sie bitte hier Ihren Fortschritt.
2 08.07.2024 - 02.09.2024
  • Research for resources and links on how to programme Jetracer using MATLAB/ROS2
  • programme Jetracer using MATLAB
  • Use of ROS2 to teach the Jetson Nano.

Dokumentieren Sie bitte hier Ihren Fortschritt.

Cuda 10.2 set path

Dokumentieren Sie bitte hier Ihren Fortschritt.

dpkg: error processing package nvidia-l4t-bootloader

Dokumentieren Sie bitte hier Ihren Fortschritt.

Nvcc not Found

Dokumentieren Sie bitte hier Ihren Fortschritt.

Install Cudnn

Dokumentieren Sie bitte hier Ihren Fortschritt.

SDL 1.2 installation

Dokumentieren Sie bitte hier Ihren Fortschritt.

No publick key(update error)

Dokumentieren Sie bitte hier Ihren Fortschritt.