Pseudo-Measurements in a Decentralized Cooperative Localization

Abstract

This paper proposes the cooperative use of pseudo-measurements in a decentralized extended Kalman filter (DEKF) based localization algorithm for multi-robot systems. The filter utilizes proprioceptive (i.e., Inertial Measurement Unit (IMU)) and exteroceptive (i.e., Ultra-Wideband (UWB)) measurements to improve the localization performance of the system in the presence of a degraded GNSS environment. The contribution of this work is to evaluate the benefits of using pseudo-measurement updates, such as zero-velocity update (ZUPT) and zero-angular rate update (ZARU), in a DEKF-based localization algorithm and compare different heuristics of deciding when to utilize pseudo-measurements in a multi-robot system.