A Generalized Extended Kalman Filter Implementation for the Robot Operating System

Moore, T. and Stouch, D.

Presented at the 13th International Conference on Intelligent Autonomous Systems (IAS 13), Padova, Italy (July 2014)

Accurate state estimation for a mobile robot often requires the fusion of data from multiple sensors. Software that performs sensor fusion should therefore support the inclusion of a wide array of heterogeneous sensors. This paper presents a software package, robot_localization, for the Robot Operating System (ROS). The package currently contains an implementation of an extended Kalman filter (EKF). It can support an unlimited number of inputs from multiple sensor types, and allows users to customize which sensor data fields are fused with the current state estimate. In this work, we motivate our design decisions, discuss implementation details, and provide results from real-world tests.


For More Information

To learn more or request a copy of a paper (if available), contact Tom Moore.

(Please include your name, address, organization, and the paper reference. Requests without this information will not be honored.)