TUM Course - "Artificial Intelligence in Automotive Technology" - Lecture 6

TUM Course - "Artificial Intelligence in Automotive Technology" - Lecture 6
Topic: Path Finding: From British Museum to A*
Lecturer: Lennart Adenaw

Welcome to the TUM course "Artificial Intelligence in Automotive Technology". In 13 different lectures we will teach you the foundations of Artificial Intelligence with regard to its use in automotive technology. After each lecture will have and additional practice session where we provide coding examples for the discussed methods. Beside these videos you can find the course material (.pdf and .pptx) we made for this lecture on the homepage of the Institute of Automotive Technology from the Technical University of Munich: https://www.ftm.mw.tum.de/index.php?i...
The additional coding material for the practice session in each lecture can be found on our Github Repository: https://github.com/TUMFTM/Lecture_AI_...

Lecture Overview:
Lecture 1 - Introduction: Artificial Intelligence:    • TUM Course - "Artificial Intelligence in A...  
Lecture 2 - Computer Vision:    • TUM Course - "Artificial Intelligence in A...  
Lecture 3 - Supervised Learning: Regression:    • TUM Course - "Artificial Intelligence in A...  
Lecture 4 - Supervised Learning: Classification:    • TUM Course - "Artificial Intelligence in A...  
Lecture 5 - Unsupervised Learning: Clustering:    • TUM Course - "Artificial Intelligence in A...  
Lecture 6 - Path Finding: From British Museum to A* :    • TUM Course - "Artificial Intelligence in A...  
Lecture 7 - Introduction Neuronal Networks:    • TUM Course - "Artificial Intelligence in A...  
Lecture 8 - Deep Neural Networks:    • TUM Course - "Artificial Intelligence in A...  
Lecture 9 - Convolutional Neuronal Networks:    • TUM Course - "Artificial Intelligence in A...  
Lecture 10 - Recurrent Neuronal Networks:    • TUM Course - "Artificial Intelligence in A...  
Lecture 11 - Reeinforcement Learning:    • TUM Course - "Artificial Intelligence in A...  
Lecture 12 - AI-Development:    • TUM Course - "Artificial Intelligence in A...  
Lecture 13 - Guest Lecturer Rasmus Rothe:    • TUM Course - "Artificial Intelligence in A...  

Content of this Lecture:
5:03 Navigation
16:51 Modelling street with graphs
46:32 Search trees
50:44 Path finding algorithms (DFS, BFS, Best First, Dijkstra, A*)
1:27:21 Application
1:30:56 Summary
1:32:49 Exercise (Generate a routable graph and find the path with different algorithms)