Autonomous Road Surveying - Versionsgeschichte

Ulrich.schneider@hshl.de am 7. März 2025 um 10:37 Uhr

2025-03-07T10:37:50Z

← Nächstältere Version		Version vom 7. März 2025, 10:37 Uhr
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	* [https://www.springerprofessional.de/en/lane-detection-in-autonomous-vehicles-using-ai/25954814 Lane Detection in Autonomous Vehicles Using AI]		* [https://www.springerprofessional.de/en/lane-detection-in-autonomous-vehicles-using-ai/25954814 Lane Detection in Autonomous Vehicles Using AI]
	* [https://hbz-hhl.primo.exlibrisgroup.com/permalink/49HBZ_HHL/pmh7h/alma991001255230906482 Artificial Intelligence for Autonomous Vehicles : The Future of Driverless Technology.]		* [https://hbz-hhl.primo.exlibrisgroup.com/permalink/49HBZ_HHL/pmh7h/alma991001255230906482 Artificial Intelligence for Autonomous Vehicles : The Future of Driverless Technology.]
			* [https://matlabacademy.mathworks.com MATLAB Academy]

	= Repository =		= Repository =

Ulrich.schneider@hshl.de: /* Task list */

2025-03-07T10:11:37Z

Task list

← Nächstältere Version		Version vom 7. März 2025, 10:11 Uhr
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	# Set up requirements for the system		# Set up requirements for the system
	# Research on solutions for the task		# Research on solutions for the task
	# Implementation in MATLAB<sup>®</sup>. Teach a AI to drive in the right lane. Input are video and steering angle		# Implementation in MATLAB<sup>®</sup>. Teach an AI to drive in the right lane. Input are video and steering angle
	# Evaluation of the solutions using a morphological box ([https://en.wikipedia.org/wiki/Morphological_box Zwicky box])		# Evaluation of the solutions using a morphological box ([https://en.wikipedia.org/wiki/Morphological_box Zwicky box])
	# Implementation the most promising on the [[JetRacer]]		# Implementation the most promising on the [[JetRacer]]

Ulrich.schneider@hshl.de: /* Introduction */

2025-03-04T14:57:18Z

Introduction

← Nächstältere Version		Version vom 4. März 2025, 14:57 Uhr
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	= Introduction =		= Introduction =
	A model car (scale 1:20) equipped with a camera should drive autonomously in the right lane. Usually this is done by image processing. In this bachelor thesis steering angle and video are used to train an artificial intelligence (AI) to drive autonomously on the track (see Fig. 1)		A model car (scale 1:10) equipped with a camera should drive autonomously in the right lane. Usually this is done by image processing. In this bachelor thesis steering angle and video are used to train an artificial intelligence (AI) to drive autonomously on the track (see Fig. 1)

	= Task list =		= Task list =

Ulrich.schneider@hshl.de am 4. März 2025 um 08:01 Uhr

2025-03-04T08:01:41Z

← Nächstältere Version		Version vom 4. März 2025, 08:01 Uhr
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	# Research on solutions for the task		# Research on solutions for the task
	# Implementation in MATLAB<sup>®</sup>. Teach a AI to drive in the right lane. Input are video and steering angle		# Implementation in MATLAB<sup>®</sup>. Teach a AI to drive in the right lane. Input are video and steering angle
	# Evaluation of the solutions using a morphological box ([https://en.wikipedia.org/wiki/Morphological_box Zwicky box)		# Evaluation of the solutions using a morphological box ([https://en.wikipedia.org/wiki/Morphological_box Zwicky box])
	# Implementation the most promising on the [[JetRacer]]		# Implementation the most promising on the [[JetRacer]]
	# CAD design and 3D printing of prism mount for the [[JetRacer]]		# CAD design and 3D printing of prism mount for the [[JetRacer]]

Ulrich.schneider@hshl.de: /* Knowledge Requirements */

2025-02-28T07:42:34Z

Knowledge Requirements

← Nächstältere Version		Version vom 28. Februar 2025, 07:42 Uhr
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	= Knowledge Requirements =		= Knowledge Requirements =
	The project requires prior knowledge in some but not all of the following subject areas. If you do not meet the requirements, the task can be individually adapted based on your previous knowledge.		The project requires prior knowledge in some but not all of the following subject areas. If you do not meet the requirements, the task can be individually adapted based on your previous knowledge.
	* Model making (e.g. woodworking, metalworking, CAD, 3D printing)		* Model making (e. g. woodworking, metalworking, CAD, 3D printing)
	* MATLAB<sup>®</sup>/Simulink		* MATLAB<sup>®</sup>/Simulink
	* Robotics		* Robotics
	* Control technology ~~(line tracker)~~		* Control technology
	* Document versioning with SVN		* Document versioning with SVN
	* Documentation with Word and in the HSHL Wiki.		* Documentation with Word and in the HSHL Wiki.

Ulrich.schneider@hshl.de: /* Getting started */

2025-02-27T10:18:50Z

Getting started

← Nächstältere Version		Version vom 27. Februar 2025, 10:18 Uhr
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	* [https://de.mathworks.com/videos/matlab-and-simulink-robotics-arena-deep-learning-with-nvidia-jetson-and-ros--1542015526909.html Deep Learning with MATLAB, NVIDIA Jetson, and ROS]		* [https://de.mathworks.com/videos/matlab-and-simulink-robotics-arena-deep-learning-with-nvidia-jetson-and-ros--1542015526909.html Deep Learning with MATLAB, NVIDIA Jetson, and ROS]
	* [https://de.mathworks.com/matlabcentral/answers/2072946-matlab-to-control-jetracer-jetson-nano-tx1-motor/?s_tid=ans_lp_feed_leaf FAQ: Matlab to control jetracer(jetson nano tx1) motor]		* [https://de.mathworks.com/matlabcentral/answers/2072946-matlab-to-control-jetracer-jetson-nano-tx1-motor/?s_tid=ans_lp_feed_leaf FAQ: Matlab to control jetracer(jetson nano tx1) motor]
	* [[JetRacer]]		* [[JetRacer\| Wiki article: JetRacer]]
	* [https://github.com/NVIDIA-AI-IOT/jetracer NVidia: JetRacer]		* [https://github.com/NVIDIA-AI-IOT/jetracer NVidia: JetRacer]
	* [https://www.formulaedge.org/what-is-jetracer formulaedge.org]		* [https://www.formulaedge.org/what-is-jetracer formulaedge.org]

Ulrich.schneider@hshl.de: /* Getting started */

2025-02-27T10:16:49Z

Getting started

← Nächstältere Version		Version vom 27. Februar 2025, 10:16 Uhr
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	* [https://www.thinkautonomous.ai/blog/lane-detection/ Lane Detection: The 3 types of Deep Learning (non-OpenCV) algorithms]		* [https://www.thinkautonomous.ai/blog/lane-detection/ Lane Detection: The 3 types of Deep Learning (non-OpenCV) algorithms]
	* [https://www.irjmets.com/uploadedfiles/paper//issue_6_june_2023/42644/final/fin_irjmets1688121553.pdf Automatic Lane Line Detection using AI]		* [https://www.irjmets.com/uploadedfiles/paper//issue_6_june_2023/42644/final/fin_irjmets1688121553.pdf Automatic Lane Line Detection using AI]
	* https://www.springerprofessional.de/en/lane-detection-in-autonomous-vehicles-using-ai/25954814 Lane Detection in Autonomous Vehicles Using AI]		* [https://www.springerprofessional.de/en/lane-detection-in-autonomous-vehicles-using-ai/25954814 Lane Detection in Autonomous Vehicles Using AI]
			* [https://hbz-hhl.primo.exlibrisgroup.com/permalink/49HBZ_HHL/pmh7h/alma991001255230906482 Artificial Intelligence for Autonomous Vehicles : The Future of Driverless Technology.]

	= Repository =		= Repository =

Ulrich.schneider@hshl.de: /* Getting started */

2025-02-27T10:15:40Z

Getting started

← Nächstältere Version		Version vom 27. Februar 2025, 10:15 Uhr
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	* S<span style="font-variant:small-caps">chreiber</span>, C.: ''KI-gestützte „Follow-Me“-Funktion am Beispiel des JetRacer''. Mittweida, Hochschule Mittweida – University of Applied Sciences, Fakultät Ingenieurwissenschaften, Masterarbeit, 2023. URL: [https://monami.hs-mittweida.de/frontdoor/deliver/index/docId/14754/file/MA_55114_Christian-Schreiber_geschwaerzt.pdf]		* S<span style="font-variant:small-caps">chreiber</span>, C.: ''KI-gestützte „Follow-Me“-Funktion am Beispiel des JetRacer''. Mittweida, Hochschule Mittweida – University of Applied Sciences, Fakultät Ingenieurwissenschaften, Masterarbeit, 2023. URL: [https://monami.hs-mittweida.de/frontdoor/deliver/index/docId/14754/file/MA_55114_Christian-Schreiber_geschwaerzt.pdf]
	* [https://www.thinkautonomous.ai/blog/lane-detection/ Lane Detection: The 3 types of Deep Learning (non-OpenCV) algorithms]		* [https://www.thinkautonomous.ai/blog/lane-detection/ Lane Detection: The 3 types of Deep Learning (non-OpenCV) algorithms]
			* [https://www.irjmets.com/uploadedfiles/paper//issue_6_june_2023/42644/final/fin_irjmets1688121553.pdf Automatic Lane Line Detection using AI]
			* https://www.springerprofessional.de/en/lane-detection-in-autonomous-vehicles-using-ai/25954814 Lane Detection in Autonomous Vehicles Using AI]

	= Repository =		= Repository =

Ulrich.schneider@hshl.de: /* Getting started */

2025-02-27T10:11:07Z

Getting started

← Nächstältere Version		Version vom 27. Februar 2025, 10:11 Uhr
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	* [https://pypi.org/project/lazypredict/ Diese Library ist aus unserer Erfahrung ganz gut, um erst einmal den vielversprechendsten Algorithmus für die Test-Daten zu finden]		* [https://pypi.org/project/lazypredict/ Diese Library ist aus unserer Erfahrung ganz gut, um erst einmal den vielversprechendsten Algorithmus für die Test-Daten zu finden]
	* S<span style="font-variant:small-caps">chreiber</span>, C.: ''KI-gestützte „Follow-Me“-Funktion am Beispiel des JetRacer''. Mittweida, Hochschule Mittweida – University of Applied Sciences, Fakultät Ingenieurwissenschaften, Masterarbeit, 2023. URL: [https://monami.hs-mittweida.de/frontdoor/deliver/index/docId/14754/file/MA_55114_Christian-Schreiber_geschwaerzt.pdf]		* S<span style="font-variant:small-caps">chreiber</span>, C.: ''KI-gestützte „Follow-Me“-Funktion am Beispiel des JetRacer''. Mittweida, Hochschule Mittweida – University of Applied Sciences, Fakultät Ingenieurwissenschaften, Masterarbeit, 2023. URL: [https://monami.hs-mittweida.de/frontdoor/deliver/index/docId/14754/file/MA_55114_Christian-Schreiber_geschwaerzt.pdf]
			* [https://www.thinkautonomous.ai/blog/lane-detection/ Lane Detection: The 3 types of Deep Learning (non-OpenCV) algorithms]

	= Repository =		= Repository =

Ulrich.schneider@hshl.de: /* Getting started */

2025-02-27T10:01:45Z

Getting started

← Nächstältere Version		Version vom 27. Februar 2025, 10:01 Uhr
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	*[[Anforderungen_an_eine_wissenschaftlich_Arbeit\| Requirements for a scientific work]]		*[[Anforderungen_an_eine_wissenschaftlich_Arbeit\| Requirements for a scientific work]]
	= Getting started =		= Getting started =
	* [[Lane_Keeping_with_AI\| Wiki ~~acticle~~: Lane Keeping with AI]]		* [[Lane_Keeping_with_AI\| Wiki article: Lane Keeping with AI]]
	* [https://de.mathworks.com/videos/deploying-deep-neural-networks-to-gpus-and-cpus-using-matlab-coder-and-gpu-coder-1567105707114.html?s_tid=abt_vid_pers_recs_nonen Deploying Deep Neural Networks to GPUs and CPUs Using MATLAB Coder and GPU Coder]		* [https://de.mathworks.com/videos/deploying-deep-neural-networks-to-gpus-and-cpus-using-matlab-coder-and-gpu-coder-1567105707114.html?s_tid=abt_vid_pers_recs_nonen Deploying Deep Neural Networks to GPUs and CPUs Using MATLAB Coder and GPU Coder]
	* [https://de.mathworks.com/videos/matlab-and-simulink-robotics-arena-deep-learning-with-nvidia-jetson-and-ros--1542015526909.html Deep Learning with MATLAB, NVIDIA Jetson, and ROS]		* [https://de.mathworks.com/videos/matlab-and-simulink-robotics-arena-deep-learning-with-nvidia-jetson-and-ros--1542015526909.html Deep Learning with MATLAB, NVIDIA Jetson, and ROS]