Abstract
An advantage of Moving Horizons Estimation in contrast with the previously tested Extended Kalman Filter is presented in the context of achieving a useful form of teach/repeat for wheelchairs of severely disabled veterans within their homes. The ability to combine numerical integrals of the measured wheel rotations of the chair with chair-mounted cameras and camera-based observations of wall-mounted fiducials within a trailing, selected “window” based on the “taught” trajectory, in order to precisely and reliably repeat that trajectory, is presented. The importance and real-time feasibility of the observation-batch-selection protocol—which is applied both to the teaching data and, in real time, to the tracking data—is discussed. Experimental illustration uses the trajectory shown in https://youtu.be/7Yrc3IuXBus.
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Acknowledgment
This research was supported in part by the US Department of Veterans Affairs, and in part by the Naval Center for Applied Research in Artificial Intelligence, US Office of Naval Research.
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Skaar, S.B. (2018). Moving Horizons Estimation for Wheelchair Trajectory Repeatability in the Home. In: Ruffa, A., Toni, B. (eds) Advanced Research in Naval Engineering. STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health. Springer, Cham. https://doi.org/10.1007/978-3-319-95117-1_6
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