Adaptive Extended Kalman Filter for Indoor/Outdoor Localization using a 802.15.4a Wireless Network

Authors - A. Benini, A. Mancini, E. Frontoni, P. Zingaretti, S. Longhi.

Abstract - Indoor and outdoor localization of mobile robots using wireless technologies is very attractive in many applications as cooperative robotics. Wireless networks can be successfully used not only for communication among heterogeneous vehicles (e.g., ground, aerial) but also for localization of a mobile robot using IEEE 802.15.4a devices with ranging capability based on Symmetrical Double-Sided Two Way Ranging (SDS-TWR). This technique tries to overtake the limitations of the classical one Received Signal Strength Indication (RSSI) (e.g., Wi-fi mapping) that does not ensure good performance especially in structured environments. The set of these devices allows to create a Wireless Sensor Network (WSN) that is suitable for cooperative tasks where the data link is fundamental to share data and support the relative localization. In this paper an Adaptive Extended Kalman Filter (EKF) is introduced as a possible technique to improve the localization in both outdoor and indoor environments also in real time due to a reduced computational complexity. The proposed approach allows to model the bias of ranging data considering also the faults in the measurements. The obtained results put in evidence the necessity of further ranging data to obtain centimetric accuracy and precision of localization that actually is rated to 1m.

This paper is available on ECMR Proceedings.

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