Udemy - Advanced Kalman Filtering and Sensor Fusion

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size2.6 GB
  • Uploaded Byfreecoursewb
  • Downloads25
  • Last checkedOct. 05th '21
  • Date uploadedOct. 02nd '21
  • Seeders 4
  • Leechers11

Infohash : E64CC5FF5497AACCAD4BF5DB3CEA00D8B6C5CADC

Advanced Kalman Filtering and Sensor Fusion



MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 82 lectures (8h 20m) | Size: 2.13 GB
Theory and C++ Simulation Implementation for Autonomous Vehicles and Self Driving Cars!
What you'll learn:
How to use the Linear Kalman Filter to solve linear optimal estimation problems
How to use the Extended Kalman Filter to solve non-linear estimation problems
How to use the Unscented Kalman Filter to solve non-linear estimation problems
How to fuse in measurements of multiple sensors all running at different update rates
How to tune the Kalman Filter for best performance
How to correctly initialize the Kalman Filter for robust operation
How to model sensor errors inside the Kalman Filter
How to use fault detection to remove bad sensor measurements
How to implement the above 3 Kalman Filter Variants in C++
How to implement the LKF in C++ for a 2d Tracking Problem
How to implement the EKF and UKF in C++ for an autonomous self-driving car problem

Requirements
A curious mind!
Basic Calculus: Functions, Derivatives, Integrals
Linear Algebra: Matrix and Vector Operations
Basic Probability
Basic C++ Programming Knowledge

Description
You need to learn know Sensor Fusion and Kalman Filtering! Learn how to use these concepts and implement them with a focus on autonomous vehicles in this course.

The Kalman filter is one of the greatest discoveries in the history of estimation and data fusion theory, and perhaps one of the greatest engineering discoveries in the twentieth century. It has enabled mankind to do and build many things which could not be possible otherwise. It has immediate application in control of complex dynamic systems such as cars, aircraft, ships and spacecraft.

Files:

[ CourseHulu.com ] Udemy - Advanced Kalman Filtering and Sensor Fusion
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Welcome
    • 1. Welcome to the Course.mp4 (27.4 MB)
    • 1. Welcome to the Course.srt (7.0 KB)
    • 2. Course Outline.mp4 (7.0 MB)
    • 2. Course Outline.srt (2.5 KB)
    • 3. Setting Up C++ Development Environment.mp4 (9.8 MB)
    • 3. Setting Up C++ Development Environment.srt (3.3 KB)
    • 3.1 Setting_up_the_C_Development_Environment.pdf (878.1 KB)
    • 4. Setting Up C++ Simulation.mp4 (6.3 MB)
    • 4. Setting Up C++ Simulation.srt (2.0 KB)
    • 5. C++ Simulation Readme.html (6.3 KB)
    • 6. Course Resources.html (0.4 KB)
    • 6.1 2D Vehicle EKF Prediction Step Exercise.pdf (704.8 KB)
    • 6.10 Linear Vehicle Tracker Update Step Exercise.pdf (259.2 KB)
    • 6.11 Setting up the C++ Development Environment.pdf (878.1 KB)
    • 6.12 Unscented Kalman Filter Summary.pdf (1.1 MB)
    • 6.2 2D Vehicle EKF Update Step Exercise.pdf (481.1 KB)
    • 6.3 2D Vehicle UKF Prediction Step Exercise.pdf (688.0 KB)
    • 6.4 2D Vehicle UKF Update Step Exercise.pdf (391.7 KB)
    • 6.6 Extended Kalman Filter Summary.pdf (750.7 KB)
    • 6.7 Linear Kalman Filter Summary.pdf (445.9 KB)
    • 6.8 Linear Vehicle Tracker Initial Conditions Exercise.pdf (248.6 KB)
    • 6.9 Linear Vehicle Tracker Prediction Step Exercise.pdf (444.6 KB)
      • AKFSF-Simulation-CPP
      • AKFSF-Simulation.gif (1.5 MB)
      • CMakeLists.txt (0.6 KB)
      • LICENSE (34.3 KB)
      • README.md (5.3 KB)
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