Package Summary

pose_ekf_slam

Author: Narcis palomeras
License: BSD
Source: git https://github.com/narcispr/pose_ekf_slam (branch: None)

Contents

Package Summary
1. How to use Pose EKF-SLAM
  1. pose_ekf_slam
  2. test_pose_ekf_slam
2. More information

Package Summary

Package pose-ekf-slam is a modular localization and mapping system for 6DoF vehicles. Standard navigation messages as PoseWithCovarianceStamped, TwistWithCovarianceStamped, and Imu sensor messages are combined by means of an extended Kalman filter. This node is capable of estimating vehicle position and linear velocity as well as the position of detected landmarks in real-time. It is entirely written in python for ROS Fuerte. It's philosophy is similar to package robot_pose_ekf but with several enchancements.

Author: Narcís Palomeras
License: BSD
Source: git https://github.com/narcispr/pose_ekf_slam

How to use Pose EKF-SLAM

Package pose_ekf_slam contains two nodes:

pose_ekf_slam.py
test_pose_ekf_slam.py

pose_ekf_slam

This node receive position fixes of type PoseWithCovarianceStamped in the topic

/pose_ekf_slam/pose_update

linear velocity updates of type TwistWithCovarianceStamped are received through the topic

/pose_ekf_slam/velocity_update

and vehicle orientation and angular velocity are expected at

/pose_ekf_slam/imu_input

using an Imu sensor message. Finally, landmark updates have to be published at

/pose_ekf_slam/landmark_update/landmark_id

in order to be discovered by the pose_ekf_slam node. They are also PoseWithCovarianceStamped messages.

Outputs of this node are an Odometry message published at

/pose_ekf_slam/odometry

and a custom message, indicating the position and covariance of each landmark, published at

/pose_ekf_slam/map

test_pose_ekf_slam

This node can be used to test pose_ekf_slam but the main idea is to be modified for every user in order to transform their navigation messages, with position, twist or landmarks information, into the kind of messages expected by the pose_ekf_slam node.

More information

More information about this node can be found at:

N. Palomeras, S. Nagappa, D. Ribas, N. Gracias and M. Carreras. Vision-based localization and mapping system for AUV intervention. OCEANS'13 MTS/IEEE. Bergen, 2013.