This project is an implementation of a Sensor Fusion Module between LIDAR and RADAD sensors for tracking an object; using the Extended Kalman Filter Algorithm.
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Updated
Oct 20, 2017 - C++
This project is an implementation of a Sensor Fusion Module between LIDAR and RADAD sensors for tracking an object; using the Extended Kalman Filter Algorithm.
C++ Library for INS-GPS Extended-Kalman-Filter (Error State Version)
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Extended Kalman Filter Localization Lab using ROS
Master Thesis on processing point clouds from Velodyne VLP-16 LiDAR sensors with PCL in ROS to improve localization method, based on Extended Kalman Filter.
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React.js App for autonomous robot using Extended Kalman FIlter (EKF) and PID controller.
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using hloc for loop closure in OpenVINS
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ekfFusion is a ROS package for sensor fusion using the Extended Kalman Filter (EKF). It integrates IMU, GPS, and odometry data to estimate the pose of robots or vehicles. With ROS integration and support for various sensors, ekfFusion provides reliable localization for robotic applications.
A monocular plane-aided visual-inertial odometry
Kálmán filter based ROS 1 / ROS 2 node (geometry_msgs/pose, sensor_msgs/imu)
An open source platform for visual-inertial navigation research.
IMU + X(GNSS, 6DoF Odom) Loosely-Coupled Fusion Localization based on ESKF, IEKF, UKF(UKF/SPKF, JUKF, SVD-UKF) and MAP
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