Sensor Fusion
Filters: KF, EKF, UKF || Process Models: CV, CTRV || Measurement Models: Radar, Lidar
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Tracking With Extended Kalman Filter | 451 | 3 years ago | 5 | mit | C++ | |||||
| Object (e.g Pedestrian, vehicles) tracking by Extended Kalman Filter (EKF), with fused data from both lidar and radar sensors. | ||||||||||
| Datmo | 225 | 7 months ago | 3 | bsd-2-clause | C++ | |||||
| Detection and Tracking of Moving Objects (DATMO) using sensor_msgs/Lidar. | ||||||||||
| Tracking With Unscented Kalman Filter | 100 | 3 years ago | 2 | C++ | ||||||
| Object (e.g Pedestrian, biker, vehicles) tracking by Unscented Kalman Filter (UKF), with fused data from both lidar and radar sensors. | ||||||||||
| Sfnd_3d_object_tracking | 73 | 2 years ago | C++ | |||||||
| Icpslam | 37 | 5 years ago | 1 | C++ | ||||||
| A basic SLAM system that employs 2D and 3D LIDAR measurements | ||||||||||
| Xv11lidar_stm32f429 | 32 | 10 years ago | gpl-2.0 | C | ||||||
| Neato XV-11 LIDAR connected to an STM32F429IDISCOVERY board for 360-degree range scanning and measurement | ||||||||||
| Sensor Fusion | 21 | 5 years ago | 5 | gpl-3.0 | C++ | |||||
| Filters: KF, EKF, UKF || Process Models: CV, CTRV || Measurement Models: Radar, Lidar | ||||||||||
| Udaicty Carnd State Estimation 02 Lidar And Radar Fusion With Ekf | 19 | 4 years ago | C++ | |||||||
| Udacity Self-Driving Car Engineer Nanodegree - Term 2 - Lesson 6 - Lidar and Radar Fusion with EKF in C++. | ||||||||||
| Extended Kalman Filter | 14 | 4 years ago | mit | C++ | ||||||
| Sensor fusion algorithm using LiDAR and RADAR data to track moving object, predicting and updating dynamic state estimation. | ||||||||||
| Velodyne | 13 | 7 years ago | mit | Python | ||||||
| Velodyne Lidar Python Library | ||||||||||
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