Course 3 falls under the workshop series Self-driving Cars & AI and focuses on the analysis, explanation and synthesis of algorithms for: 

  1. Environment perception from visual data
  2. Construction of a map of an unknown area
  3. Finding the optimal route
  4. Autonomous navigation using a map 

Note: Participation in the cycle does not require the completion of the other cycles of the project. 

Course 3 consists of the following sessions:

Session 1: General Cycle Description and Introduction to Graph Theory

General description of cycle 3 and a brief introduction to Python programming language. Description of the problem of finding the shortest path and basic introduction to graph theory. 

Session 2: Introduction to Neural Networks

Introduction to the artificial neuron (perceptron) and multi-layer neural networks. Methodology for training a neural network. Implementation and execution of a neural network using TensorFlow/Keras libraries.

Session 3: Intersection Recognition with AI

Data collection for recognizing the basic characteristics of the route. Design and implementation of a CNN model for environment perception with final goal of training and applying the model in practice. 

Session 4: Algorithms for Finding the Optimal Route

Introduction to basic pathfinding algorithms (DFS, BFS, Dijkstra, and A*). Programming and implementation of pathfinding algorithms. 

Session 5: Creating a Map of an Unknown Area

Mapping using intersections. Creation of a graph of the map and data collection via remote control to construct the map. 

Session 6: Autonomous Vehicle Navigation Following the Route

Introduction to autonomous vehicle navigation with an AI algorithm and creation of a complete system (map, intersection recognition, optimal route, and control commands). Final experimental testing of the complete system. 

References - Supplementary Material 

  1. https://www.python.org/
  2. https://jupyter.org/
  3. https://www.tensorflow.org/
  4. https://www.w3schools.com/python/
  5. https://www.learnpython.org/
  6. https://www.pythontutorial.net/
  7. Neural Network
  8. Graph_Theory
  9. D3 Grath Theory
  10. Algorithm Dijkstra
  11. Algorithm Α*
  12. Pathfinding Visualizer #1
  13. Pathfinding Visualizer #2

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