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Msckf

Multi-State Constraint Kalman Filter with ROS interface.

Install / Use

/learn @leokoppel/Msckf
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

MSCKF

Experimental implementation of the Multi-State Constraint Kalman Filter with ROS interface.

Based on the paper by Mourikis and Roumeliotis (PDF).

Also includes a feature tracking node using OpenCV's SIFT implementation.

This is a work in progress. In particular, The API is a bit non-standard and is subject to change.

ROS nodes

feature_tracking_node

Subscribed topics

  • camera/image_rect (sensor_msgs/Image) - Undistorted image stream.
  • camera/camera_info (sensor_msgs/CameraInfo) - The corresponding camera metadata.

Published topics

  • output_image (sensor_msgs/Image) - Image with arrows drawn on it, showing matches.
  • features (msckf/ImageFeatures) - custom message describing feature positions

msckf_node

Subscribed topics

  • imu_vel (geometry_msgs/TwistStamped) - IMU measurement of linear and angular velocity.
  • odom (nav_msgs/Odometry) - Position of robot, used to initialize the filter
  • camera/image_rect (sensor_msgs/Image)- the same image stream used by feature_tracking_node. Currently, only the header information is used.
  • features (msckf/ImageFeatures) - the feature information published by feature_tracking_node

Published topics

  • odom_combined (geometry_msgs/PoseWithCovarianceStamped) - Estimated robot pose

Related Skills

View on GitHub
GitHub Stars124
CategoryDevelopment
Updated19d ago
Forks56

Languages

C++

Security Score

80/100

Audited on Mar 6, 2026

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