Self-driving Car Nano-degree. Term 2: Sensor Fusion. Project 2: Unscented Kalman Filter
-
Updated
Nov 21, 2017 - C++
Self-driving Car Nano-degree. Term 2: Sensor Fusion. Project 2: Unscented Kalman Filter
UKF project for Udacity SDCND term 2
State Estimation of a 3D Quad with the use of Bayes Rules (Extended Kalman Filter)
A hardware and software sensor framework for automotive data collection based on Raspberry Pi.
List of Projects pertaining to Udacity's world famous "Self Driving Car Engineer Nanodegree" Program.
Hands-on Laboratory exercises on 8085 and AVR boards for "Microprocessors Laboratory" course in NTUA
A course project developed with a focus to build an experimental setup for persistent pipe monitoring robot that detects leaks in underground water pipes.
A user-friendly toolkit for engineers and researchers to address the problem of aligning measurements from gyroscopes mounted on the same rigid body.
Using Unscented Kalman Filters to Fuse the Measurements Recorded by LIDAR and RADAR sensors of a Self Driving Car
Extended Kalman Filter for self-driving cars with noisy LIDAR and RADAR measuremets in c++
Path Planner for self-driving cars in highway traffic
Sensor Fusion Camera Final Project Submission
Mobile Robot Development
Built a navigation stack using two different sensors - GPS & IMU, understand their relative strengths + drawbacks, and get an introduction to sensor fusion.
Notes I took/used for passing Sensor Fusion Nanodegree
Self-driving Car Nano-degree. Term 2: Sensor Fusion. Project 1: Extended Kalman Filter
Extended Kalman Filters
Sensor Fusion - Udacity's Self Driving Car Nanodegree
Udacity Flying Car Nanodegree Project #4: Quadrotor 3D Estimation
Add a description, image, and links to the sensor-fusion topic page so that developers can more easily learn about it.
To associate your repository with the sensor-fusion topic, visit your repo's landing page and select "manage topics."