Autonomous Car – Learning Algorithms

Genetic algorithm and Backpropagation in autonomous cars

Autonomous cars need learning in order to recognize their environment and behave consistently. Neural networks give us the opportunity to develop complex behaviors and tasks like driving.

I have implemented two algorithms that are widely used in machine learning: backpropagation (supervised learning) and genetic algorithm (reinforcement learning).

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LiDAR: Autonomous Car

LiDAR implementation in self-driving cars

LiDAR (Light Imaging, Direction And Ranging) is a method that measures the distance to a target by illuminating the target with pulsed laser light and measuring the reflected pulses with a sensor. Autonomous cars take advantage of this new technology.

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Chemistry Studio 2019 ©

Molecular Chemistry Simulator & Editor

This application allows you to create molecules with bonds between atoms. There is no need a further background in chemistry, it has an intuitive user interface and only a few instructions of use:

  • New: This creates a new molecule.
  • Add: adds new atom to the atom selected.
  • Atom Type: enable you to select atoms in a wide variety of them.
  • Delete: deletes the molecule.

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Self Driving Car in Unreal Engine 4

Autonomous car: learning and testing process.

Description

Pages: 25

Author: Daniel López Montero

Abstract

AI is a new field that appeared a few decades ago and has seen unprecedented growth. The AI approach has been used in numerous fields, such as finance, medicine, music, customer service, and transportation. Some of the big challenges we have to cope with are the computing power and lack of documentation. Big companies such as Google and Apple do not share advances in this field, the secretism characterizes this scientific field and thus the information we can get is very restrictive. In this work, we introduce a model of an autonomous car and then examine different algorithms capable of driving the car in a simulated. We also discuss the difficulties we need to deal with such as local minimums, losing diversity, fitness functions, localization, performance, and future applications.

Keywords

Artificial intelligence, neural network, genetic algorithm, backpropagation, self-driving car.

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Electromagnetic Simulator

Magnetic and Electrosatatic simulator in UE4 and C++

Lorentz force

In physics (particularly in electromagnetism) the Lorentz force (or electromagnetic force) is the combination of electric and magnetic force on a point charge due to electromagnetic fields. A particle of charge q moving with a velocity v in an electric field E and a magnetic field B experiences a force.

    \[\vec{F}=q\vec{E} +q\vec{v}\times \vec{B} \]

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