Mutual localization using anonymous bearing measurements

This paper addresses the problem of mutual localization in multi-robot systems in presence of anonymous (i.e., without the identity information) bearing-only measurements. The solution of this problem is relevant for the design and implementation of any decentralized multi-robot algorithm/control. A novel algorithm for probabilistic multiple registration of these measurements is presented, where no global localization, distances, or identity are used. With respect to more conventional solutions that could be conceived on the basis of the current literature, our method is theoretically suitable for tasks requiring frequent, many-to-many encounters among agents (e.g., formation control, cooperative exploration, multiple-view environment sensing). An extensive experimental study validates our method and compares it with the full-informative case of bearing-plus-distance measurements. The results show that the proposed localization system exhibits an accuracy commensurate to our previous method [1] which uses bearing-plus-distance information

Mutual Localization in a Multi-Robot System with Anonymous Relative Position Measures

We address the mutual localization problem for I multi-robot system, under the assumption that each robot is equipped with a sensor that provides a measure of the relative position of nearby robots without their identity. Anonymity generates a combinatorial ambiguity in the Inversion of the measure equations, leading to a multiplicity of admissible relative pose hypotheses. To solve the problem, we propose a two-stage localization system based on MultiReg, an innovative algorithm that computes on-line all the possible relative pose hypotheses, whose output is processed by a data associator and a multiple EKF to isolate and refine the best estimates. The performance of the mutual localization system is analyzed through experiments, proving the effectiveness of the method and, in particular, its robustness with respect to false positives (objects that look like robots) and false negatives (robots that are not detected) of the measure process

Analysis of radiofrequency-based methods for position and velocity determination of autonomous robots in lunar surface exploration missions

The use of distributed systems has been disruptive in almost any industrial sector, from manufacturing to processing plants from environmental monitoring to vehicle control, and many more. It is therefore natural to assess the benefits that such an advantageous engineering paradigm could bring to space exploration. In recent years, we have been witness to the emergence of concepts such as fractionated satellite systems, formation flying, megaconstellations, and femtoswarms. Most of these space missions have evolved from the idea of a decentralization of processes that were formerly performed in platforms conceived as monolithic systems. The application of this concept to robotic systems is not new, and a great deal of scientific contributions on multi-robot systems exists, focusing on different aspects such as cooperative robotics, behavioural or reactive control, distributed artificial intelligence, swarm multi-agent systems etc. The intrinsic advantages of distribution (improved reliability and efficiency, higher robustness, etc.) has been boosted by the exponential growing of computational power density and a simultaneous miniaturization of technology, leading to smaller and more powerful robotic platforms, which could make a distributed robotic system, made of small robotic agents, a powerful substitute to classical large robotic platforms. This thesis proposes, in the framework of multi-robot systems, a localization method for robotic agents in planetary surface exploration scenarios based on RF range and Doppler frequency shift analysis. The relevance of spatial localization awareness in agents belonging to a distributed robotic system is defined in the context of the advantages of robotic exploration. Different range determination techniques and, specifically, the advantages of including Doppler Effect in the determination of the relative position within the robotic system deployed are considered and the strengths and weaknesses analysed accordingly. Special attention is devoted to the noise sources present in the lunar environment, related to a practical (i.e. non-ideal) implementation architecture and its influence on the system performance. From this point of view, we develop a theoretical model for localization accuracy estimation, generated from power spectrum characteristics, in accordance with the system architecture proposed, and consolidated with numerical simulations and a parametrical assessment on a set of real references of components playing a key role in the overall performance. The selected system architecture is then implemented in a representative set-up and tested under laboratory conditions. Algorithms used for carrier frequency generation and frequency measurement are developed, applied and tested in the hardware-on-the-loop breadboard. The results show that Doppler frequency component can be measured with the proposed architecture, yielding a high sensitivity in the determination of relative speed even at standard communication frequencies (UHF), and improving significantly at higher bands (S, C, etc.). This enables the possibility of adding relative speed to relative position determination via sensor fusion techniques, improving the response time and accuracy during navigation through the exploration scenario

Localización de robots móviles de recursos limitados basada en fusión sensorial por eventos

Uno de los aspectos esenciales en la robótica móvil es la obtención y procesamiento de la información relativa a la localización del robot en el espacio de movimiento, con el fin utilizarla para generar los movimientos deseados del robot. Para esto se busca utilizar la mayor cantidad posible de fuentes de información con el fin de corregir los errores de posición asociados a la presencia de ruido en las mediciones del robot. La fusión de esta información es tema central de la tesis en la cual se exponen distintos algoritmos de fusión, desarrollados específicamente para robots móviles con recursos de computación limitados. Utilizando modelos dinámicos en conjunto con técnicas de fusión basadas en filtro de Kalman se realiza una estimación local de la posición utilizando sensores inerciales. Esta estimación se fusiona mediante un filtro de Kalman con información de un sensor global y una corrección basada en eventos. Esta combinación de filtros en cascada con corrección basada en eventos es el principal aporte de la presente tesis. Esta solución al problema de localización permite una precisión similar pero un coste computacional menor a esquemas más complejos de fusión, lo que permite su implementación en robots de recursos limitados. El esquema propuesto se extiende para permitir la localización cooperativa de grupos de robots, modificando la actualización por eventos para incorporar la fusión de la posición de distintos robots cercanos entre si. Para esto se determina la posición entre los robots y se utiliza un sistema de comunicación y gestión basada en agentes. Este método permite realizar una fusión sensorial inteligente, tomando en cuenta únicamente la información de posición más fiable para actualizar al grupo de robots, lo que nuevamente reduce el costo computacional de la solución sin repercusiones considerables en la precisión de la localización. Los algoritmos propuestos son probados extensivamente mediante simulación y en distintas plataformas, principalmente en el LEGO NXT. Se presentan además ejecuciones de tiempo extendido que comprueban la estabilidad y robustez del método en largas distancias.Marin Paniagua, LJ. (2014). Localización de robots móviles de recursos limitados basada en fusión sensorial por eventos [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/38902TESI