Indoor localisation is currently regarded as one of the most useful services offered to human beings and robotics agents, as it can support a variety of applications. Among all the possible sensing solutions developed to address this problem (which is usually made challenging by the complex, heterogeneous and crowded nature of indoor environments), RFID systems based on passive tags are very promising due to their relatively low cost and the ease of deployment. In this paper, a theoretical analysis of the localisation problem using Ultra High Frequency (UHF) RFID tags for mobile robots is considered. The feasibility of the proposed approach is demonstrated by analysing the local nonlinear observability of the system at hand, despite the inherent ambiguity of the phase of backscattered RF signals, which can be measured by a system installed on the moving agent. The validity of the analysis and the practicality of this localisation approach is further confirmed by using a position tracking estimator based on an Unscented Kalman Filter (UKF).
Robot localisation based on phase measures of backscattered UHF-RFID signals
Motroni A.;Nepa P.;Buffi A.;Tellini B.
2019-01-01
Abstract
Indoor localisation is currently regarded as one of the most useful services offered to human beings and robotics agents, as it can support a variety of applications. Among all the possible sensing solutions developed to address this problem (which is usually made challenging by the complex, heterogeneous and crowded nature of indoor environments), RFID systems based on passive tags are very promising due to their relatively low cost and the ease of deployment. In this paper, a theoretical analysis of the localisation problem using Ultra High Frequency (UHF) RFID tags for mobile robots is considered. The feasibility of the proposed approach is demonstrated by analysing the local nonlinear observability of the system at hand, despite the inherent ambiguity of the phase of backscattered RF signals, which can be measured by a system installed on the moving agent. The validity of the analysis and the practicality of this localisation approach is further confirmed by using a position tracking estimator based on an Unscented Kalman Filter (UKF).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.