- Welcome to the Course
- Course Outline
- Setting Up C++ Development Environment
- Setting Up C++ Simulation
- C++ Simulation Readme
- Course Resources
Online
₹ 529 3,199
Quick facts
particular | details | |
---|---|---|
Medium of instructions
English
|
Mode of learning
Self study
|
Mode of Delivery
Video and Text Based
|
Course and certificate fees
Fees information
certificate availability
certificate providing authority
The syllabus
Welcome
Introduction
- What is Sensor Fusion
- How Does Sensor Fusion Work
- How Does Sensor Fusion Work Notes
- What is the Kalman Filter
- What is the Kalman Filter Notes
- Types of Kalman Filters
- Types of Kalman Filters Notes
- Learning Roadmap
- Simulation Overview
Background Theory
- Section Outline
- Basic Probability
- Basic Probability Quiz
- Probability Density Functions
- Probability Density Functions Quiz
- Multivariate Probability
- Multivariate Probability Quiz
- Gaussian Probability Density Functions
- Gaussian Probability Density Functions Quiz
- Linear Transformation of Uncertainties
- Linear Transformation of Uncertainties Quiz
- Differential Equations
- State Space Representation
- Continuous and Discrete Time
- Mathematical Models
- Discrete Time Conversions
- Probability and Estimation
Linear Kalman Filter
- How Does the Kalman Filter Work
- Simulation Framework
- Process Model
- Kalman Filter Prediction Step
- Kalman Filter Prediction Step Implementation
- Kalman Filter Prediction Step Explanation
- Kalman Filter Update Step
- Kalman Filter Update Step Implementation
- Kalman Filter Update Step Explanation
- Kalman Filter Initial Conditions
- Kalman Filter Summary
Extended Kalman Filter
- What is the Extended Kalman Filter
- EKF Simulation Framework
- 2D Vehicle Process Model
- EKF Prediction Step (Summary)
- What are Jacobians
- EKF Prediction Step (Derivation)
- EKF Prediction Step (Example)
- EKF 2D Vehicle Filter Prediction Step
- EKF 2D Vehicle Filter Prediction Step Explanation
- Lidar Measurement Model
- EKF Measurement Innovation (Summary)
- EKF Measurement Innovation (Derivation)
- EKF Measurement Innovation (Example)
- EKF Update Step (Summary)
- EKF Update Step (Derivation)
- EKF Update Step (Example)
- EKF 2D Vehicle Filter Update Step
- EKF 2D Vehicle Filter Update Step Explanation
- Numerical Jacobian Calculation
- Numerical Jacobian Calculation Example
- EKF Understanding and Insights
- Extended Kalman Filter Summary
Unscented Kalman Filter
- What is the Unscented Kalman Filter
- Unscented Transformation
- UKF Simulation Framework
- UKF Prediction Step (Summary)
- Matrix Square Root
- UKF 2D Vehicle Filter Prediction Step
- UKF 2D Vehicle Filter Prediction Step Explanation
- UKF Measurement Innovation (Summary)
- UKF Update Step (Summary)
- UKF Update Step (Derivation)
- UKF 2D Vehicle Filter Update Step
- UKF 2D Vehicle Filter Update Step Explanation
- Unscented Kalman Filter Summary
Filtering in the Real World
- Sensor Models and Errors
- Dealing with Faulty Data
- Dealing with Sensor Biases
- Dealing with Initial Conditions
Capstone Project
- Project Overview
- Project Details and Framework
- Project Hints
Conclusion
- Summary
- Bonus
Instructors
Mr Steven Dumble
Aerospace Engineer
Freelancer