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https://github.com/iamfaisalkhan/kalman-filters
Extended Kalman Filter implementation for tracking an object in 2D.
https://github.com/iamfaisalkhan/kalman-filters
Last synced: 3 days ago
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Extended Kalman Filter implementation for tracking an object in 2D.
- Host: GitHub
- URL: https://github.com/iamfaisalkhan/kalman-filters
- Owner: iamfaisalkhan
- Created: 2017-05-02T15:15:15.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2017-05-02T21:41:03.000Z (over 7 years ago)
- Last Synced: 2024-11-15T21:37:26.879Z (3 days ago)
- Language: C++
- Homepage:
- Size: 2.43 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Extended Kalman Filter
---An implementation of kalman filter for predicting and tracking the position and velocity of a moving object in a 2D world. The tracking is done using the input from two sensors:
* Laser (LIDAR)
* RADARThe LIDAR sensor measures only the position of the object. The RADAR sensor provides measurement for the range (radial distance $$\rho$$ from the origin), bearing (angle between x-axis and the range vector and also the radial velocity (change of $$\rho$$).
In this project, we use the Kalman Filter (KF) to combine the measurements from these two sensor to predict a 4D state of the moving object that includes its position and its velocity.
## Dependencies
* cmake >= 3.5
* All OSes: [click here for installation instructions](https://cmake.org/install/)
* make >= 4.1
* Linux: make is installed by default on most Linux distros
* Mac: [install Xcode command line tools to get make](https://developer.apple.com/xcode/features/)
* Windows: [Click here for installation instructions](http://gnuwin32.sourceforge.net/packages/make.htm)
* gcc/g++ >= 5.4
* Linux: gcc / g++ is installed by default on most Linux distros
* Mac: same deal as make - [install Xcode command line tools]((https://developer.apple.com/xcode/features/)
* Windows: recommend using [MinGW](http://www.mingw.org/)## Basic Build Instructions
1. Clone this repo.
2. Make a build directory: `mkdir build && cd build`
3. Compile: `cmake .. && make`
* On windows, you may need to run: `cmake .. -G "Unix Makefiles" && make`
4. Run it: `./ExtendedKF path/to/input.txt path/to/output.txt`. You can find
some sample inputs in 'data/'.
- eg. `./ExtendedKF ../data/obj_pose-laser-radar-synthetic-input.txt`