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.
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Notes
- 1.
The bag file generated from this experiment is available at http://www.cra.com/robot_localization_ias13.zip.
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Moore, T., Stouch, D. (2016). A Generalized Extended Kalman Filter Implementation for the Robot Operating System. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds) Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-319-08338-4_25
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DOI: https://doi.org/10.1007/978-3-319-08338-4_25
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