Sensor-based globally asymptotically stable range-only simultaneous localization and mapping

Range-only simultaneous localization and mapping is addressed in this paper, through the design, analysis, and experimental validation of a globally asymptotically stable (GAS) filter. A nonlinear sensor-based system is designed and its dynamics augmented so that the proposed formulation can be considered as linear time-varying for the purpose of observability analysis. This allows the establishment of observability results related to the original nonlinear system that naturally lead to the design of a Kalman filter with GAS error dynamics. The performance of the proposed algorithm is assessed resorting to a set of realistic simulations and to the results obtained from experimental tests.

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