Course 2: Self-driving Car & Autonomous Navigation

Workshop Series | Ages: 14+

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Ticket prices
Total course cost: 80€

Age of participants
14+

Duration
120 minutes

Instructors
Nikos Zourtsanos, Dimitris Piperidis

Days and times
Group Α: 12/10, 19/10, 02/11, 09/11, 16/11, 23/11, 30/11, 07/12, time 15:45 – 17:45

for Schools:

No events

for Public:

No events for the week 16/12 - 22/12

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No events

Course 2 falls under the workshop series Self-driving Cars & AI and focuses on the analysis, explanation and synthesis of:

- Algorithms for processing data acquired from a camera
- Autonomous vehicle control algorithms using visual feedback
- Artificial Intelligence algorithms for autonomous navigation and decision-making.

Course 2 consists of the following seminars:

Session 1: General Cycle Description and Introduction to Computer Vision
Cycle 2 overview, brief introduction to Python programming language, introduction to OpenCV computer vision library.

Session 2: Image Processing Algorithms
Image/video acquisition from the autonomous vehicle camera, fundamental image processing algorithms, implementation of algorithms using OpenCV.

Session 3: Vehicle Control Using Visual Feedback
Lane detection algorithms, introduction to PID control, vehicle motion control using PID.

Session 4: Introduction to Neural Networks
Introduction to artificial neuron (perceptron) and multi-layer neural networks, neural network training methodology, neural network implementation and execution using TensorFlow/Keras libraries.

Session 5: Introduction to CNNs
Introduction to convolutional neural networks, implementation of a classification example with pre-trained CNN, implementation and training of a classification example with CNN.

Session 6: Autonomous Vehicle Navigation Using AI I
Introduction to Udacity's open source simulator, introduction to NVIDIA's CNN for self-driving cars, implementation of NVIDIA's CNN in the simulator (part I).

Session 7: Autonomous Vehicle Navigation Using AI II
Implementation of NVIDIA CNN in the simulator (Part II), Image/Control Signal Data Acquisition, Data Processing and Augmentation.

Session 8: Autonomous Vehicle Navigation Using AI III
Training and extracting the network model, implementing the CNN network based on the trained model and sending control signals to the vehicle, applying the integrated AI algorithm to a vehicle operating in a real track.

References - Supplementary Material