Udacity Self-Driving Car Engineer Nanodegree projects.
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Updated
Mar 28, 2023 - C++
Udacity Self-Driving Car Engineer Nanodegree projects.
Multiple Object Tracker, Based on Hungarian algorithm + Kalman filter.
solution of exercises of the book "probabilistic robotics"
Fusing GPS, IMU and Encoder sensors for accurate state estimation.
LiDAR SLAM = FAST-LIO + Scan Context
Unscented Kalman Filter library for state and parameter estimation
IMU - FreeIMU Library Zero Drift, Altitude & LSM303 Heading Stability
A small collection of Kalman Filters on Lie groups
An unscented Kalman Filter implementation for fusing lidar and radar sensor measurements.
Kalman filter, sensor fusion
A real-time, direct and tightly-coupled LiDAR-Inertial SLAM for high velocities with spinning LiDARs
Repository for Eye Gaze Detection and Tracking
real time video stabilization using Kalman Filter
Loosely coupled integration of GNSS and IMU
Filters: KF, EKF, UKF || Process Models: CV, CTRV || Measurement Models: Radar, Lidar
A compact realtime embedded Attitude and Heading Reference System (AHRS) using Recursive Least Squares (RLS) for magnetometer calibration and EKF/UKF for sensor fusion on Arduino platform
An extended Kalman Filter implementation in C++ for fusing lidar and radar sensor measurements.
Implement Kalman filter for your Arduino projects
C++ implementation of BoT-SORT MOT algorithm with Re-ID and Camera Motion Compensation
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