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A Generalized Extended Kalman Filter Implementation for the Robot Operating System

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 302)

Abstract

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.

Keywords

Sensor fusion Extended kalman filter Localization Robot operating system 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Sensor Processing and Networking DivisionCharles River Analytics, Inc.CambridgeUSA

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