An open source platform for visual-inertial navigation research.
-
Updated
May 31, 2024 - C++
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
Fusing GPS, IMU and Encoder sensors for accurate state estimation.
Accurate 3D Localization for MAV Swarms by UWB and IMU Fusion. ICCA 2018
A monocular plane-aided visual-inertial odometry
using hloc for loop closure in OpenVINS
Interface for OpenVINS with the maplab project
Self-position estimation by eskf by measuring gnss and imu
C++ Library for INS-GPS Extended-Kalman-Filter (Error State Version)
Secondary posegraph adapted for interfacing with OpenVINS, based on VINS-Mono / VINS-Fusion.
This project builds a ROS-based Autonomous Robot from scratch
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.
Kálmán filter based ROS 1 / ROS 2 node (geometry_msgs/pose, sensor_msgs/imu)
Extended Kalman Filter Localization Lab using ROS
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.
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.
Rowbot is an autonomous rover. It is currently a small scale prototype. My goal is to go bigger!
React.js App for autonomous robot using Extended Kalman FIlter (EKF) and PID controller.
Add a description, image, and links to the ekf-localization topic page so that developers can more easily learn about it.
To associate your repository with the ekf-localization topic, visit your repo's landing page and select "manage topics."