Bayes Filter

This repository contains implementations of various types of Bayes filters.

It contains implementations for

1. Kalman Filter
2. Extended Kalman Filter
3. Unscented Kalman Filter
4. Particle Filter

It also includes the following examples:

1. Spring mass damper system (kf, efk, ukf, pf)
2. Simple pendulum (kf, ekf, ukf, pf)

NOTE: The kalman filter example in the non-linear simple pendulum example has been added to demonstrate the performance of the kalman filter when the measurement to state space conversion, the process matrix and the control matrix are non-linear and approximations/assumptions are made to help it replicate the actual process (in this case, the small angle approximation)

To build and run

 git clone https://github.com/vss2sn/bayes_filter.git  
 sudo apt install libeigen3-dev
 cd bayes_filter  
 mkdir build  
 cd build  
 cmake .. && make -j  
 ./main # or the examples' executables

To run without C++20

Please checkout the branch c++17 and use that/rebase on it

TODO

1. Add documentation
2. Option for dimension correctness checking (esp. for control input)
3. Add options for resampling n particle filter
4. Add calculation for the error covariance in the particle filter

References

1. https://github.com/tysik/kalman_filters/
2. https://github.com/PrieureDeSion/kalmanfilter-cpp/