Abstract
This paper presents a climbing robot, with wheeled locomotion and adhesion through permanent magnets. This machine was developed to be used in the inspection of several types of man-made ferromagnetic structures, such as towers for wind turbines, fuel storage tanks, ship hulls, etc., in order to, for instance, detect weaknesses due to corrosion. In this article are presented the main aspects taken into consideration for its design, as well as several constructive aspects, among which are detailed its mechanical and electrical construction, the implemented control architecture and the Human-Machine Interface (HMI) for its control. The distinguishing characteristic of this robot is its dynamic adjustment system of the permanent magnets to assure the machine adhesion to the surfaces when crossing slightly irregular and curved surfaces with a large radius. © 2013, Springer Science+Business Media Dordrecht.

Abstract
This paper investigates the research profiles, collaboration patterns and research topic trends which can be identified in the proposals submitted to the ECHORD (European Clearing House for Open Robotics Development) FP7 project. On a country level, clusters were identified and characterized by patterns of proposal production per inhabitant, score and international cooperation. Belgium and Sweden constitute a cluster characterized by high proposal production, with very high scores and extensive international collaboration. Belgium also excels from another cluster analysis, being as the only country where 100% of proposals involve industry-academia cooperation and obtain scores above 10. Other findings show that single partner proposals have significantly lower quality than multi-partner proposals but, on the other hand, the number of countries involved shows no influence on the quality of the proposals. Despite the high number of industrial participants present on the proposals, it is observed that they play secondary roles in the proposals, with a very low number projects leaded by companies. Also, it is observed that partnerships between research institutions (non-universities) are the most successful. Concerning topics of the proposals, the technology human-robot interface and the product vision robot for small-scale manufacturing are the most significant. Finally, the paper shows clusters of institutions extracted from the giant network of relations obtained from the ECHORD set of proposals.

Abstract
This paper presents an interactive programming method for programming industrial robots in ceramic applications. The main purpose was to develop a simple but flexible programming system that empowers the user with product driven programming without compromising flexibility. To achieve this flexibility, a two step hybrid programming model was designed: first the user sketches the desired trajectory in a spatial augmented reality programming table using the final product and then relies on an advanced 3D graphical system to tune the robot trajectory in the final workcell. The results measured by the end-user feedback show that a new level of flexibility was reached for this type of application.

Abstract
This article focuses on the localization and navigation of a mobile differential robot in an indoor office-like environment. These are fundamental issues to service robotics, which is a branch with a strong market growth. The work implements a vision tracking system, environment mapping, route planning and navigation for an autonomous robot application inside services buildings. One goal of the methodology is its application with low cost equipment. The test bed chosen was a Pioneer P3-DX robot [16] in a service building, with an attached USB webcam, pointed at the ceiling to take advantage of the position of the light fixtures as natural landmarks. The robot location is estimated through two distinct probabilistic methods: a particle filter, when there is no information about the starting location of the robot, and the Kalman filter, given the convergence of the particle filter. Both methods use the detection of light fixtures together with the robot kinematics as information to estimate the pose. The mapping of the environment and its obstacles is obtained from the localization estimates and the information gathered by ultrasound sensors, representing the entire navigation space discretized in the form of an occupation grid. Planning the navigation path is determined by a simple search algorithm, namely the Wavefront algorithm, based on the information contained in the occupancy grid. For a given path, navigation is performed with obstacle avoidance using the virtual forces method. Replanning is used to recover from local minima situations.

Abstract
The diffusion of innovation theory aims to explain how new ideas and practices are disseminated among social system members. A significant number of the existing models is based on the use of parameters which determine the process of innovation adoption, and rely on simple mathematical functions centered in the observation and description of diffusion patterns. These models enable a more explicit diffusion process study, but their use involves the estimation of diffusion coefficients, usually obtained from historical data or chronological series. This raises some application problems in contexts where there is no data or the data is insufficient. This paper proposes the use of evolutionary computation as an alternative approach for the simulation of innovation diffusion within organizations. To overcome some of the problems inherent to existing models an evolutionary algorithm is proposed based on a probabilistic approach. The results of the simulations that were done to validate the algorithm revealed to be very promissing in this context. Simulation experiment results are presented that reveals a very promising approach of the proposed model. © 2013 Springer-Verlag Berlin Heidelberg.

Abstract
In complexity theory, scheduling problem is considered as a NP-complete combinatorial optimization problem. Since Multi-Agent Systems manage complex, dynamic and unpredictable environments, in this work they are used to model a scheduling system subject to perturbations. Meta-heuristics proved to be very useful in the resolution of NP-complete problems. However, these techniques require extensive parameter tuning, which is a very hard and time-consuming task to perform. Based on Multi-Agent Learning concepts, this article propose a Case-based Reasoning module in order to solve the parameter-tuning problem in a Multi-Agent Scheduling System. A computational study is performed in order to evaluate the proposed CBR module performance. © 2013 Springer-Verlag Berlin Heidelberg.