Eduardo Munera

Dynamic Reconfiguration of a RGBD Sensor Based on QoS and QoC Requirements in Distributed Systems

The inclusion of embedded sensors into a networked system provides useful information for many applications. A Distributed Control System (DCS) is one of the clearest examples where processing and communications are constrained by the client’s requirements and the capacity of the system. An embedded sensor with advanced processing and communications capabilities supplies high level information, abstracting from the data acquisition process and objects recognition mechanisms. The implementation of an embedded sensor/actuator as a Smart Resource permits clients to access sensor information through distributed network services. Smart resources can offer sensor services as well as computing, communications and peripheral access by implementing a self-aware based adaptation mechanism which adapts the execution profile to the context. On the other hand, information integrity must be ensured when computing processes are dynamically adapted. Therefore, the processing must be adapted to perform tasks in a certain lapse of time but always ensuring a minimum process quality. In the same way, communications must try to reduce the data traffic without excluding relevant information. The main objective of the paper is to present a dynamic configuration mechanism to adapt the sensor processing and communication to the client’s requirements in the DCS. This paper describes an implementation of a smart resource based on a Red, Green, Blue, and Depth (RGBD) sensor in order to test the dynamic configuration mechanism presented.

A Hierarchical Hybrid Architecture for Mission-Oriented Robot Control

In this work is presented a general architecture for a multi physical agent network system based on the coordination and the behaviour management. The system is organised in a hierarchical structure where are distinguished the individual agent actions and the collective ones linked to the whole agent network. Individual actions are also organised in a hybrid layered system that take advantages from reactive and deliberative control. Sensing system is involved as well in the behaviour architecture improving the information acquisition performance.

Smart device definition and application on embedded system: performance and optimi-zation on a RGBD sensor

Embedded control systems usually are characterized by its limitations in terms of computational power and memory. Although this systems must deal with perpection and actuation signal adaptation and calculate control actions ensuring its reliability and providing a certain degree of fault tolerance. The allocation of these tasks between some different embedded nodes conforming a distributed control system allows to solve many of these issues. For that reason is proposed the application of smart devices aims to perform the data processing tasks related with the perception and actuation and offer a simple interface to be configured by other nodes in order to share processed information and raise QoS based alarms. In this work is introduced the procedure of implementing a smart device as a sensor as an embedded node in a distributed control system. In order to analyze its benefits an application based on a RGBD sensor implemented as an smart device is proposed.

Control kernel in smart factory environments: Smart resources integration

The evolution of the definition of industry into the Smart factories has provide a big improvements in terms of production efficiency and promoted new ways to implement interfaces between humans and machines. A factory plan, which is achieved by means of a set of missions, implies a set of control missions. In this work is introduced how to achieve these control missions into a smart factory through distributed services. These services are provided by integrating smart resources. Smart resources will rely its execution on the control kernel which provides real-time support and reliability to the execution of control tasks. As a conclusions, we introduce a scalable and reusable hierarchy to perform factory plans based on distributed services.

CKMultipeer: Connecting Devices Without Caring about the Network

In the current context of distributed systems, the communications have moved from a model based on connected nodes, to a model that must connect processes, or including connect data. There are many paradigms, mechanisms and architectures to give support to these distributed systems. Most of these mechanisms are extensions or evolutions of distributed node based architecture where the knowledge about the physical node is necessary. To isolate communications from the physical aspects of distributed systems a middleware, centered on the data, and oriented to connect processes has been developed. The middleware, called “CKMultipeer”, allows processes to communicate data between them. Communication is integrated without worrying about the network configuration and management. This article describes the implementation of the middleware, as well as the tests developed. Through the design of a graphical interface, the communications performance is analyzed.

Smart Resource Integration on ROS-Based Systems: Highly Decoupled Resources for a Modular and Scalable Robot Development

Nowadays robots are evolving from using a central computer unit with high computation capability to a distributed system configuration. Most cases present a robot formed with a central unit, which manages and distributes several specific tasks to some embedded systems on-board. Now these embedded systems are also evolving to more complex systems that are developed not only for executing simple tasks but offering some advanced algorithms just as complex data processing, adaptive execution, or fault-tolerance and alarm rising mechanisms. Smart Resources topology has been raised to manage abstract resources which execution relies on a physical embedded hardware. These resources are defined as a list of distributed services that can configure its execution within a context and quality requirements. Therefore this work introduces how a robot can take the advantage by making use of these Smart Resources. In order to provide a more general implementation Smart Resources are integrated into the ROS (Robot Operating System). As a result robots can make use of all the functions and mechanisms provided by the ROS and the distribution, reliability and adaptability of the Smart Resources. Finally, these advantages are reviewed by implementing a Smart Resource into a robot platform that is running ROS. In addition it is also addressed the flexibility and scalability of implementation by combining real and simulated devices into the same platform. As a result it will be summarized all the advantages of this integration and the potential application and upgrades that can be introduced into the system.

Optimizations on semantic environment management: An application for humanoid robot home assistance

This article introduces some optimization mechanisms focused on environment management, object recognition, and environment interaction. Although the generality of the presented system, this work will be focused on its application on home assistance humanoid robots. For this purpose, a generic environment formalization procedure for semantic scenery description is introduced. As the main contribution of this work, some techniques for a more efficient use of the environment knowledge are proposed. That way, the application of an area-based discrimination mechanism will avoid to process large amounts of data, useless in the current context, improving the object recognition, and characterizing the available interactions in the current area. Finally, the formalized description, and the optimization procedure, will be tested and verified on a specific home scenario using a humanoid robot.

Limited Resources Management in a RoboCup Team Vision System

The vision system provides to a humanoid robot the most complete information about the environment, having thus visual information extraction a great influence in the decision process of interaction with the environment. It represents one of the most resources consumer in the system, so it has to be efficiently designed without compromising the reliability of the provided information. Software implementation of an accurate vision system is one of the more distinctive elements in RoboCup competitions, especially in the RoboCup, where normative is becoming more and more restrictive and no hardware modifications can be made. In embedded control systems, management of the available resources is crucial to achieve a good performance and get the most from them. Focusing on the Robocup SPL, Nao robot has the CPU as the main shared and limited resource and, to a lesser degree, wireless network and memory should also be considered. In this work, the design of the vision module and the ability of the Hidalgos Team architecture to cope with limited resources are presented. The goal is to maximise CPU utilisation by boosting the capacities of the vision system, while maintaining control properties such as reactivity and stability. A first strategy emphasises on reducing resources consumed by the vision system through adaptability to control requirements. A second strategy focuses on adapting the execution rates of the modules, and especially of the vision system, to the available resources.