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This paper deals with the problem of humanoid robot localization and proposes a new method for position estimation that has been developed for the RoboCup Standard Platform League environment. Firstly, a complete vision system has been implemented in the Nao robot platform that enables the detection of relevant field markers. The detection of field markers provides some estimation of distances for the current robot position. To reduce errors in these distance measurements, extrinsic and intrinsic camera calibration procedures have been developed and described. To validate the localization algorithm, experiments covering many of the typical situations that arise during RoboCup games have been developed: ranging from degradation in position estimation to total loss of position (due to falls, ‘kidnapped robot’, or penalization). The self-localization method developed is based on the classical particle filter algorithm. The main contribution of this work is a new particle selection strategy. Our approach reduces the CPU computing time required for each iteration and so eases the limited resource availability problem that is common in robot platforms such as Nao. The experimental results show the quality of the new algorithm in terms of localization and CPU time consumption.

Abstract. This paper introduces how a mobile robot can perform navigation tasks by taking the advantages of implementing a control kernel middleware (CKM) based system. Smart resources are also included into the topology of the system for improving the distribution of computational load of the needed tasks. The CKM and the smart resources are both highly reconfigurable, even on execution time, and they also implement fault detection mechanisms and QoS policies. By combining of these capabilities, the system can be dinamically adapted to the requirements of its tasks. Furthermore, this solution is suitable for most type of robots, including those which are provided of a low computational power because of the distribution of load, the benefits of exploiting the smart resources capabilities, and the dynamic performance of the system.

Home environments are changing as more technological devices are used to improve daily life. The growing demand for high technology in our homes means that robot integration will soon arrive. Home devices are evolving in a connected paradigm in which data flows to perform efficient home task management. Heterogeneous home robots connected in a network can establish a workflow that complements their capabilities and so increases performance within a mission execution. This work addresses the definition and requirements of a robot-group mission in the home context. The proposed solution relies on a network of smart resources, which are defined as cyber-physical systems that provide high-level service execution. Firstly, control middleware architecture is introduced as the execution base for the Smart resources.Next, the Smart resource topology and its integration within a robotic platform are addressed. Services supplied by Smart resources manage their execution through a robot behavior architecture. Robot behavior execution is hierarchically organized through a mission definition that can be established as an individual or collective approach. Environment model and interaction tasks characterize the operation capabilities of each robot within a mission. Mission goal achievement in a heterogeneous group is enhanced through the complement of the interaction capabilities of each robot. To offer a clearer explanation, a full use case is presented in which two robots cooperate to execute a mission and the previously detailed steps are evaluated. Finally, some of the obtained results are discussed as conclusions and future works is introduced. ResumenLos entornos domésticos se encuentran sometidos a un proceso de cambio gracias al empleo de dispositivos tecnológicos que mejoran la calidad de vida de las personas. La creciente demanda de alta tecnología en los hogares señala una próxima incorporación de la robótica de servicio. Los dispositivos domésticos están evolucionando hacia un paradigma de conexión en el cual la información fluye para ofrecer una gestión más eficiente. En este entorno, robots heterogéneos conectados a la red pueden establecer un flujo de trabajo que ofreciendo nuevas soluciones y incrementando la eficiencia en la ejecución de tareas. Este trabajo aborda la definición y los requisitos necesarios para la ejecución de misiones en grupos de robots heterogéneos en entornos domésticos. La solución propuesta se apoya en una red de Smart resources, que son definidos como sistemas ciber-físicos que proporcionan servicios de alto nivel. En primer lugar, se presenta la arquitectura del middleware de control en la cual se basa la ejecución de los Smart resources. A continuación se detalla la topología de los Smart resources, así como su integración en plataformas robóticas. Los servicios proporcionados por los Smart resources gestionan su ejecución mediante una arquitectura de comportamientos para robots. La ejecución de estos comportamientos se organiza de forma jerárquica mediante la definición de ...