MaRS: A Modular and Robust Sensor-Fusion Framework
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Updated
Apr 23, 2025 - C++
MaRS: A Modular and Robust Sensor-Fusion Framework
Sensor fusion between IMU, GNSS and Lidar data using an Error State Extended Kalman Filter.
A ROS wrapper for the MaRS Library
Matlab implementations of various multi-sensor labelled multi-Bernoulli filters
A ROS2 wrapper for the MaRS Library
EKF model to estimate humanoid state (pose + velocities) based on floating base dynamics equations.
C++ Core and ROS 2 Node for Full-State (Navigation) Filter.
Comprehensive notes and implementations from Monte Carlo Statistical Methods (2nd Ed.), focusing on Bayesian inference, filtering, smoothing, and state estimation using Monte Carlo and MCMC techniques.
Implementation of Linear/Nonlinear filters in MATLAB
A comprehensive autonomous UAV framework integrating real-time SLAM, dynamic trajectory planning, and precision attitude control for navigation in complex environments.
Implimentation of kalman filter for a vehicle with unknown location, noisy measurements using python
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