Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision

Mobile robots need autonomy to fulfill their tasks. Such autonomy is related whith their capacity to explorer and to recognize their navigation environments. In this context, the present work considers techniques for the classification and extraction of features from images, using artificial neural networks. This images are used in the mapping and localization system of LACE (Automation and Evolutive Computing Laboratory) mobile robot. In this direction, the robot uses a sensorial system composed by ultrasound sensors and a catadioptric vision system equipped with a camera and a conical mirror. The mapping system is composed of three modules; two of them will be presented in this paper: the classifier and the characterizer modules. Results of these modules simulations are presented in this paper.

Multivalued adaptive neuro-fuzzy controller for robot vehicle - art. no. 1406

Robotic vehicle navigation in unstructured and uncertain environments is still a challenge. This paper presents the implementation of a multivalued neurofuzzy controller for autonomous ground vehicle (AGVs) in indoor environments. The control system consists of a hierarchy of mobile robot using multivalued adaptive neuro-fuzzy inference system behaviors.

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.

Communication that values patient autonomy is associated with satisfaction with care: a systematic review

Question: Which communication factors used by clinicians during patient-clinician interactions are associated with satisfaction with care? Design: Systematic review with meta-analysis of studies investigating the association of verbal or nonverbal factors or interaction styles used by clinicians with patient satisfaction during an encounter between clinician and patient. Participants: Clinicians interacting with patients in primary care or rehabilitation settings. Results: Twenty-seven studies investigated 129 verbal, nonverbal, and interaction style factors. of these, 38 factors were consistently associated with satisfaction. Verbal factors concerning clinicians involving, facilitating, and supporting patients were associated with satisfaction with care. Most communication factors presented a fair correlation (r >= 0.21 but < 0.41) with satisfaction with care. Nonverbal factors such as time spent discussing prevention and time spent reading patient charts had a fair association with satisfaction with care (correlations range from 0.21 to 0.40). A moderate association was found between interaction styles such as caring (pooled r = 0.51, 95% CI 0.42 to 0.60) and satisfaction with care. Over half (58%) of the 129 identified factors never associated with satisfaction with care and the remainder associated inconsistently. Conclusion: The number of potential modifiable communication factors associated with satisfaction with care and the magnitude of their association partially support interventions to train clinicians in communication skills that value patient autonomy. [Oliveira VC, Refshauge KM, Ferreira ML, Pinto RZ, Beckenkamp PR, Negrao Filho RF, Ferreira PH (2012) Communication that values patient autonomy is associated with satisfaction with care: a systematic review. Journal of Physiotherapy 58: 215-229]

Brazilian foreign policy in the Cardoso era: The search for autonomy through integration

The Fernando Henrique Cardoso administration attempted to replace a reactive foreign policy agenda dominated by a logic of autonomy through distance with a proactive international agenda guided by a logic of autonomy through integration. In adopting this agenda, the administration maintained that Brazil would be able to confront its problems and secure more control over its future if it actively contributed to elaborating the norms and guidelines of the administration of the global order. Because of structural weaknesses, however, this policy of integration, adherence, and participation was not adequately accompanied by positions entailing practical responsibilities - responsibilities that would have prepared both government and civil society for a higher profile in the post - cold-war era. In the end, the gains achieved during Cardoso's tenure failed to alter Brazil's international standing in any significant way. © 2007 Latin American Perspectives.

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.

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.

Poder y autonomía: roles cambiantes de las mujeres del Caribe = Changing power and autonomy of the Caribbean women

Incluye Bibliografía

Use of myoelectric signals to command mobile entertainment robot by disabled children: Design and control architecture

Severely disabled children have little chance of environmental and social exploration and discovery. This lack of interaction and independency may lead to an idea that they are unable to do anything by themselves. In an attempt to help children in this situation, educational robotics can offer and aid, once it can provide them a certain degree of independency in the exploration of environment. The system developed in this work allows the child to transmit the commands to a robot through myoelectric and movement sensors. The sensors are placed on the child's body so they can obtain information from the body inclination and muscle contraction, thus allowing commanding, through a wireless communication, the mobile entertainment robot to carry out tasks such as play with objects and draw. In this paper, the details of the robot design and control architecture are presented and discussed. With this system, disabled children get a better cognitive development and social interaction, balancing in a certain way, the negative effects of their disabilities. © 2012 IEEE.

Mobile Robot navigation modelling, control and applications

This work presents and discusses the main topics involved on the design of a mobile robot system and focus on the control and navigation systems for autonomous mobile robots. Introduces the main aspects of the Robot design, which is a holistic vision about all the steps of the development process of an autonomous mobile robot; discusses the problems addressed to the conceptualization of the mobile robot physical structure and its relation to the world. Presents the dynamic and control analysis for navigation robots with kinematic and dynamic model and, for final, presents applications for a robotic platform of Automation, Simulation, Control and Supervision of Mobile Robots Navigation, with studies of dynamic and kinematic modelling, control algorithms, mechanisms for mapping and localization, trajectory planning and the platform simulator. © 2012 Praise Worthy Prize S.r.l. - All rights reserved.

Fast robot voice interface through optimum-path forest

Voice-based user interfaces have been actively pursued aiming to help individuals with motor impairments, providing natural interfaces to communicate with machines. In this work, we have introduced a recent machine learning technique named Optimum-Path Forest (OPF) for voice-based robot interface, which has been demonstrated to be similar to the state-of-the-art pattern recognition techniques, but much faster. Experiments were conducted against Support Vector Machines, Neural Networks and a Bayesian classifier to show the OPF robustness. The proposed architecture provides high accuracy rates allied with low computational times. © 2012 IEEE.

A proposed neural control for the trajectory tracking of a nonholonomic mobile robot with disturbances

In this paper, a trajectory tracking control problem for a nonholonomic mobile robot by the integration of a kinematic neural controller (KNC) and a torque neural controller (TNC) is proposed, where both the kinematic and dynamic models contains disturbances. The KNC is a variable structure controller (VSC) based on the sliding mode control theory (SMC), and applied to compensate the kinematic disturbances. The TNC is a inertia-based controller constituted of a dynamic neural controller (DNC) and a robust neural compensator (RNC), and applied to compensate the mobile robot dynamics, and bounded unknown disturbances. Stability analysis with basis on Lyapunov method and simulations results are provided to show the effectiveness of the proposed approach. © 2012 Springer-Verlag.

Development of a support vector machine-based navigation system for driving a mobile robot through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by preprocessing them to extract image features. Such features are then submitted to a support vector machine in order to find out the most appropriate route. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine, which so far presented around 93% accuracy in predicting the appropriate route. © 2012 IEEE.