Acoustic Tracking System for Autonomous Robots Based on TDE and Signal Intensity

Este artículo detalla el desarrollo y evaluación de un sistema de localización acústico autónomo para robots basado en TDE e intensidad de la señal, principalmente orientado hacia aplicaciones de robótica de servicios. La estimación del tiempo de retardo se realiza mediante un arreglo de dos micrófonos. El criterio del tiempo de retardo se apoya con la intensidad de la señal de un tercer micrófono (arreglo coplanar) que permite discernir de forma precisa la localización de la fuente. Este tercer micrófono alimenta también un sistema de identificación vocal, que permite que el sistema responda sólo a comandos vocales específicos. El algoritmo de predicción opera comparando el TDE sensado frente a los valores teóricos del modelo de propagación acústica, resultados que luego son ponderados de acuerdo a la intensidad promedio de la señal. Se reporta un amplio conjunto de experimentos en laboratorio sobre un prototipo real que soportan el desempeño del sistema, mostrando errores promedio en azimut de 18.1 grados y de elevación de 7.6 grados. En particular, el análisis desarrollado a partir de la estimación permite definir las condiciones necesarias y suficientes para establecer en tiempo real una posición única en el espacio de origen, con suficiente precisión para aplicaciones de navegación autónoma.This article details the development and evaluation of an autonomous acoustic localization system for robots based on Time Delay Estimation (TDE) and signal intensity, principally aimed at robotic service applications. Time Delay Estimation is carried out through an arrangement of two microphones. The time delay criteria are supported with the signal intensity of a third microphone (coplanar arrangement), which permits discerning precisely the location of the source. This third microphone also feeds a voice identification system, which lets the system respond only to specific voice commands. The prediction algorithm operates by comparing the sensed TDE against the theoretical values of the acoustic propagation model, results that are then weighted according to the signal’s mean intensity. A broad set of laboratory experiments is reported on a real prototype that support the system’s performance, showing average errors of Azimuth of 18.1 degrees and elevation of 7.6 degrees. Particularly, the analysis conducted for the estimation permits defining the necessary and sufficient conditions to establish in real time a single position in the space of origin, with sufficient precision for autonomous navigation application

Ultra-wideband Based Indoor Localization of Mobile Nodes in ToA and TDoA Configurations

Zandian R. Ultra-wideband Based Indoor Localization of Mobile Nodes in ToA and TDoA Configurations. Bielefeld: Universität Bielefeld; 2019.This thesis discusses the utilization of ultra-wideband (UWB) technology in indoor localization scenarios and proposes system setup and evaluates different localization algorithms in order to improve the localization accuracy and stability of such systems in non-ideal conditions of the indoor environment. Recent developments and advances of technology in the areas of ubiquitous Internet, robotics and internet of things (IoT) have resulted in emerging new application areas in daily life in which localization systems are vital. The significant demand for a robust and accurate localization system that is applicable in indoor areas lacking satellites link, can be sensed. The UWB technology offers accurate localization systems with an accuracy of below 10 cm and covering the range of up to a few hundred meters thanks to their dedicated large bandwidth, modulation technique and signal power. In this thesis, the technology behind the UWB systems is discussed in detail. In terms of localization topologies, different scenarios with the focus on time-based methods are introduced. The main focus of this thesis is on the differential time of arrival localization systems (TDoA) with unilateral constellation that is suitable for robotic localization and navigation applications. A new approach for synchronization of TDoA topology is proposed and influence of clock inaccuracies in such systems are thoroughly evaluated. For localization engine, two groups of static and dynamic iterative algorithms are introduced. Among the possible dynamic methods, extended Kalman filter (EKF), H∞ and unscented Kalman filter (UKF) are discussed and meticulously evaluated. In order to tackle the non-line of sight (NLOS) problem of such systems, for detection stage several solutions which are based on parametric machine learning methods are proposed. Furthermore, for mitigation phase two solutions namely adjustment of measurement variance and innovation term are suggested. Practical results prove the efficiency and high reliability of the proposed algorithms with positive NLOS condition detection rate of more than 87%. In practical trials, the localization system is evaluated in indoor and outdoor arenas in both line of sight and non-line of sight conditions. The results show that the proposed detection and mitigation methods can be successfully applied for both small and large-scale arenas with the higher performance of the localization filters in terms of accuracy in large-scale scenarios