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Projects of Udacity Self Driving Car

Home Page: https://www.udacity.com

Jupyter Notebook 44.65% Python 0.16% CMake 0.89% Shell 0.08% C++ 47.88% C 1.00% Cuda 0.48% Fortran 4.81% JavaScript 0.03% CSS 0.02% Dockerfile 0.01%

udacity_selfdrivingcar's Introduction

Udacity_SelfDrivingCar

Udacity - Self-Driving Car NanoDegree

Introduction

This repository is for projects of Udacity's self driving car nanodegree class. :blue_car:

Projects

This course has 3 terms.

  • Term 1: Computer Vision and Deep Learning
  • Term 2: Sensor Fusion, Localization, and Control
  • Term 3: Path Planning, Concentrations, and Systems

Term 1

Main topic of Term 1 is Computer Vision and Deep learning

The contents of the course are as follows. ๐Ÿ“”

  • Introduction to Neural Network

  • Miniflow

  • Introduction to Tensorflow

  • Deep Neural Network

  • Convolutional Neural Network

  • Keras

  • Transfer Learning

  • Machine Learning and Stanley

  • Support Vector Machines

  • Decision Trees

    โ€‹

The projects of the course are as follows. ๐Ÿ“‹

  • Finding Lane lines
  • Traffic Sign Classifier
  • Behavioral Cloning
  • Advanced Lane Finding
  • Vehicle Detection and Tracking

I finished all the projects of Term 1!! Yeah~~~ ๐ŸŽ‰๐ŸŽ‰

image

Term 2

Main topic of Term 2 is Sensor fusion, Localization and Control

The contents of the course are as follows. ๐Ÿ“”

  • Introduction and Sensors

  • Kalman Filters

  • Lidar and Radar Fusion with Kalman Filters in C++

  • Unscented Kalman Filter

  • Localization Overview

  • Markov Localization

  • Motion Models

  • Particle Filters

  • Implementation of a Particle Filter

  • PID Control

  • Model Predictive Control

    โ€‹

The projects of the course are as follows. ๐Ÿ“‹

  • Extended Kalman Filter
  • Unscented Kalman Filter
  • Kidnapped Vehicle (Localization)
  • PID Control
  • Model Predictive Control

I finished all the projects of Term 2!! Yeah~~~ ๐ŸŽ‰๐ŸŽ‰

Term 3

Main topic of Term 3 is Path Planning, Concentrations and pLANNING

The contents of the course are as follows. ๐Ÿ“”

  • Search

  • Prediction

  • Behavior Planning

  • Trajectory Generation

  • Advanced Deep Learning

  • Fully Convolutional Networks

  • Scene Understanding

  • Inference Performance

  • Functional Safety

  • Introduction to Functional Safety

  • Safety Plan

  • Hazard Analysis and Risk Assessment

  • Functional Safety Concept

  • Technical Safety Concept

  • Functional Safety at the Softward and Hardware Levels

  • Autonomous Vehicle Architecture

  • Introduction to ROS

  • Packages and Catkin Workspaces

  • Writing ROS Nodes

  • Completing the Program

    โ€‹

The projects of the course are as follows. ๐Ÿ“‹

  • Path Planning Project
  • Semantic Segmentation Project
  • Functional Safety
  • System Integration Project

udacity_selfdrivingcar's People

Contributors

kyushik avatar

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