Fusing Time-of-Flight and Received Signal Strength for adaptive radio-frequency ranging

Abstract

Teams of mobile cooperative robots are ideal candidates for applications where the presence of humans is impossible or should be avoided. Knowing the positions of the robots in crucial in such scenarios. A possible solution is to derive relative positions from local communication. In this work, we propose an anchor-free online channel estimation method aimed at small multi-robot teams. By combining both the Time-of-Flight (ToF) and Received Signal Strength Indicator (RSSI) ranging, provided by the nanoLoc devices, we perform an online estimation of the indoor log-distance path loss model. This model will then be used together with an Extended Kalman Filter to track distance between every pair of units. The advantages compared to previous work are: 1) we do not use any extra sensors, since all the data is captured from the transceiver module; 2) we do not use any a priori knowledge, the channel model is estimated online, without the need of fixed anchor nodes; 3) we support the high dynamics of RSSI with the improved accuracy of ToF.