A Beam Search Method to Solve the Problem of Assignment Cells to Switches in a Cellular Mobile Network

Assigning cells to switches in a cellular mobile network is known as an NP-hard optimization problem. This means that the alternative for the solution of this type of problem is the use of heuristic methods, because they allow the discovery of a good solution in a very satisfactory computational time. This paper proposes a Beam Search method to solve the problem of assignment cell in cellular mobile networks. Some modifications in this algorithm are also presented, which allows its parallel application. Computational results obtained from several tests confirm the effectiveness of this approach and provide good solutions for large scale problems.

Reducing the gap between mobile and intelligent software agents

This paper presents an approach to integrate an artificial intelligence (AI) technique, concretely rule-based processing, into mobile agents. In particular, it focuses on the aspects of designing and implementing an appropriate inference engine of small size to reduce migration costs. The main goal is combine two lines of agent research, First, the engineering oriented approach on mobile agent architectures, and, second, the AI related approach on inference engines driven by rules expressed in a restricted subset of first-order predicate logic (FOPL). In addition to size reduction, the main functions of this type of engine were isolated, generalized and implemented as dynamic components, making possible not only their migration with the agent, but also their dynamic migration and loading on demand. A set of classes for representing and exchanging knowledge between rule-based systems was also proposed.

Paraconsistent Autonomous Mobile Robot Emmy III

This work presents some improvements regarding to the autonomous mobile robot Emmy based on Paraconsistent Annotated Evidential Logic ET. A discussion on navigation system is presented.

Development of a low-cost mobile mapping system: A South American experience

This paper presents the prototype of a low-cost terrestrial mobile mapping system (MMS) composed of a van, two digital video cameras, two GPS receivers, a notebook computer, and a sound frame synchronisation system. The imaging sensors are mounted as a stereo video camera on top of the vehicle together with the GPS antennae. The GPS receivers and the notebook computer are configured to record data referred to the vehicle position at a planned time interval. This position is subsequently transferred to the road images. This set of equipment and methods provide the opportunity to merge distinct techniques to make topographic maps and also to build georeferenced road image databases. Both vector maps and raster image databases, when integrated appropriately, can give spatial researchers and engineers a new technique whose application may realise better planning and analysis related to the road environment. The experimental results proved that the MMS developed at the São Paulo State University is an effective approach to inspecting road pavements, to map road marks and traffic signs, electric power poles, telephone booths, drain pipes, and many other applications important to people's safety and welfare. A small number of wad images have already been captured by the prototype as a consequence of its application in distinct projects. An efficient organisation of those images and the prompt access to them justify the need for building a georeferenced image database. By expanding it, both at the hardware and software levels, it is possible for engineers to analyse the entire road environment on their office computers.

Autonomous mobile robots designing for the medical trash collector task

This paper describes the UNESP robotic team in the medical trash collector task, proposed on the 5 rd IEEE Latin American Robots Competition in the LEGO category. We present our understanding of the task and discuss the proposed solution, focusing on the mechanical and computational issues of the robots. The mechanics is based on rigid body capability of transforming rotational into curvilinear movement. With respect to the computational control, the system is modeled as a reactive system with sequential transition of behaviors. A state-machine is proposed to allow this transition, and the synchronization of robotic states is guaranteed by the communication system. The proposed approach has shown itself capable of dealing with the high difficulty degree of this cooperative task. ©2006 IEEE.

Conception of wheeled mobile robots with reconfigurable control using integrate prototyping

With the fast innovation of the hardware and software technologies using rapid prototyping devices, with application in the robotics and automation, more and more it becomes necessary the development of applications based on methodologies that facilitate future modifications, updates and enhancements in the original projected system. This paper presents a conception of mobile robots using rapid prototyping, distributing the several control actions in growing levels of complexity and using resources of reconfigurable computing proposal oriented to embed systems implementation. Software and the hardware are structuralized in independents blocks, with connection through common bus. The study and applications of new structures control that permits good performance in relation to the parameter variations. This kind of controller can be tested on different platform representing the wheeled mobile robots using reprogrammable logic components (FPGA). © 2006 IEEE.

Virtual simulator for mobile robots navigation systems

This paper presents the virtual environment implementation for project simulation and conception of supervision and control systems for mobile robots, that are capable to operate and adapting in different environments and conditions. This virtual system has as purpose to facilitate the development of embedded architecture systems, emphasizing the implementation of tools that allow the simulation of the kinematic conditions, dynamic and control, with real time monitoring of all important system points. For this, an open control architecture is proposal, integrating the two main techniques of robotic control implementation in the hardware level: systems microprocessors and reconfigurable hardware devices. The implemented simulator system is composed of a trajectory generating module, a kinematic and dynamic simulator module and of a analysis module of results and errors. All the kinematic and dynamic results shown during the simulation can be evaluated and visualized in graphs and tables formats, in the results analysis module, allowing an improvement in the system, minimizing the errors with the necessary adjustments optimization. For controller implementation in the embedded system, it uses the rapid prototyping, that is the technology that allows, in set with the virtual simulation environment, the development of a controller project for mobile robots. The validation and tests had been accomplish with nonholonomics mobile robots models with diferencial transmission. © 2008 IEEE.

Environment mapping for mobile robots navigation using hierarchical neural network and omnivision

Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.

JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

Problem of assignment cells to switches in a cellular mobile network via beam search method

The problem of assigning cells to switches in a cellular mobile network is an NP-hard optimization problem. So, real size mobile networks could not be solved by using exact methods. The alternative is the use of the heuristic methods, because they allow us to find a good quality solution in a quite satisfactory computational time. This paper proposes a Beam Search method to solve the problem of assignment cell in cellular mobile networks. Some modifications in this algorithm are also presented, which allows its parallel application. Computational results obtained from several tests confirm the effectiveness of this approach to provide good solutions for medium- and large-sized cellular mobile network.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Environment for teaching and development of mobile robot systems

Using robots for teaching is one approach that has gathered good results on Middle-School, High-School and Universities. Robotics gives chance to experiment concepts of a broad range of disciplines, principally those from Engineering courses and Computer Science. However, there are not many kits that enables the use of robotics in classroom. This article describes the methodologies to implement tools which serves as test beds for the use of robotics to teach Computer Science and Engineering. Therefore, it proposes the development of a flexible, low cost hardware to integrate sensors and control actuators commonly found on mobile robots, the development of a mobile robot device whose sensors and actuators allows the experimentation of different concepts, and an environment for the implementation of control algorithms through a computer network. This paper describes each one of these tools and discusses the implementation issues and future works. © 2010 IEEE.

Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained. ©2010 IEEE.