https://github.com/nikolasent/unscented-kalman-filter

Udacity Self-Driving Car Engineer Nanodegree. Project: Unscented Kalman Filters
https://github.com/nikolasent/unscented-kalman-filter

carnd kalman-filter self-driving-car sensor-fusion unscented-kalman-filter

Last synced: about 2 months ago
JSON representation

Udacity Self-Driving Car Engineer Nanodegree. Project: Unscented Kalman Filters

• Host: GitHub
• URL: https://github.com/nikolasent/unscented-kalman-filter
• Owner: NikolasEnt
• Created: 2017-04-08T20:27:10.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2017-04-25T10:26:25.000Z (over 8 years ago)
• Last Synced: 2025-08-23T21:14:55.779Z (about 2 months ago)
• Topics: carnd, kalman-filter, self-driving-car, sensor-fusion, unscented-kalman-filter
• Language: C++
• Homepage:
• Size: 985 KB
• Stars: 11
• Watchers: 3
• Forks: 10
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

          
# Unscented Kalman Filter

This Project is the seventh task (Project 2 of Term 2) of the Udacity Self-Driving Car Nanodegree program. The main goal of the project is to apply Unscented Kalman Filter to fuse data from LIDAR and Radar sensors of a self driving car using C++.

The project was created with the Udacity [Starter Code](https://github.com/udacity/CarND-Unscented-Kalman-Filter-Project).

---

## Content of this repo

- `scr`  a directory with the project code:

  - `main.cpp` - reads in data, calls a function to run the Kalman filter, calls a function to calculate RMSE

  - `ukf.cpp` - the UKF filter itself, defines the predict function, the update function for lidar, and the update function for radar

  - `tools.cpp` - a function to calculate RMSE

- `data`  a directory with two input files, provided by Udacity

- `results`  a directory with output files

## Results 

1. Input file: *sample-laser-radar-measurement-data-1.txt*

![input 1 results](readme_img/plot1.png)

RMSE = [0.0758215, 0.0842188, 0.632344, 0.580668]

Threshold: RMSE <= [0.09, 0.09, 0.65, 0.65]

2. Input file: *sample-laser-radar-measurement-data-2.txt*

![input 2 results](readme_img/plot2.png)

RMSE = [0.194559 0.189894 0.518945 0.507547]

Threshold: RMSE <= [0.20, 0.20, 0.55, 0.55]

## Dependencies

* cmake >= v3.5

* make >= v4.1

* gcc/g++ >= v5.4

## How to run the code

Clone this repo and perform 

```

mkdir build && cd build

cmake .. && make

./ExtendedKF ../data/sample-laser-radar-measurement-data-1.txt output1.txt > input1.log

./ExtendedKF ../data/sample-laser-radar-measurement-data-2.txt output2.txt > input2.log

```