Code underlying publication: Reinforcement Learning Compensated Extended Kalman Filter for Attitude Estimation

This collection contains all code to produce the results of "Reinforcement Learning Compensated Extended Kalman Filter for Attitude Estimation," <em style="color:rgb(51, 51, 51);">2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)</em>, Prague, Czech Republic, 2021, pp. 6854-6859, doi: 10.1109/IROS51168.2021.9635963. This paper leverages reinforcement learning to compensate for the classical extended Kalman filter estimation, i.e., to learn the filter gain from the sensormeasurements. The code is written in python. To use the code, the readers could set up the Python environment according to "requirements.txt." For details, please follow "README.md".