Abstract
Over the last two decades the research and development of legged locomotion robots has grown steadily. Legged systems present major advantages when compared with 'traditional' vehicles, because they allow locomotion in inaccessible terrain to vehicles with wheels and tracks. However, the robustness of legged robots, and especially their energy consumption, among other aspects, still lag behind mechanisms that use wheels and tracks. Therefore, in the present state of development, there are several aspects that need to be improved and optimized. Keeping these ideas in mind, this paper presents the review of the literature of different methods adopted for the optimization of the structure and locomotion gaits of walking robots. Among the distinct possible strategies often used for these tasks are referred approaches such as the mimicking of biological animals, the use of evolutionary schemes to find the optimal parameters and structures, the adoption of sound mechanical design rules, and the optimization of power-based indexes.

Abstract
The paper presented herein describes the development of an advanced robotized system applied to in vitro implant dentistry research. To the biomedical community this paper shows the possibilities of industrial robots to help the research. Robots are special suitable to the biomedical field specially when integrated with advanced sensors and technologies, which may facilitate both the programming tasks and the data acquisition. Robotics researchers will find in this paper one of the first applications of programming by demonstration with real users with a novel explicit robot programming technique making use of multi-camera vision combined with speech recognition. This programming method targets users who have minimal robot experience but aims at 'teaching' the robot to execute a specific task.

Abstract
Purpose - The growing complexity of industrial robot work-cells calls for the use of advanced orchestration techniques to promote flexibility and reusability. This paper aims to present a solution based on service-oriented platforms that endorses the separation of concerns, coordination and execution. Design/methodology/approach - This paper starts with the evaluation of available tools for the orchestration and service generation. Endorsing the missing features depicted in that evaluation, the paper describes developments of concepts and software and the evaluation made. Findings - From the early evaluations made in this paper, the SCXML-based purposed language is more adapted to the industrial robotic cell scenario than existing alternatives. The generation of services allow the integration without knowledge from any programming language. Practical implications - This approach's main drawback, as described by some users, was the lack of some programming features: simple math operations and conditional statements. Originality/value - This paper fulfils two partially unsolved problems: adequate languages for orchestration of service oriented on the device level and purposes techniques for the specification of services using robot programming languages.

Abstract
In this paper we introduce a framework to represent robot task plans based on Petri nets. Our approach enables modelling a robot task, analysing its qualitative and quantitative properties and using the Petri net representation for actual plan execution. The overall model is obtained from the composition of simple models, leading to a modular approach. Analysis is applied to a closed loop between the robot controller and the environment Petri net models. We focus here on the quantitative properties, captured by stochastic Petri net models. Furthermore, we introduce a method to identify the environment and action layer parameters of the stochastic Petri net models from real data, improving the significance of the model. The framework building blocks and a single-robot task model are detailed. Results of a case study with simulated soccer robots show the ability of the framework to provide a systematic modelling tool, and of determining, through well-known analysis methods for stochastic Petri nets, relevant properties of the task plan applied to a particular environment.

Abstract
Diffusion of innovation is a research topic which has been subject to several works in the last years. The diffusion of innovation theory aims to explain how new ideas and practices are disseminated between the members of a social system. A significant part of the existing models are 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. This models enable a more explicit diffusion process study, but its use involves the estimation of diffusion coefficients, usually obtained from historical data or chronological series. This raises some problems, for instance when there is no data or it is insufficient. This paper proposes the use of evolutionary computation is an alternative approach for the simulation of innovation diffusion within organizations, in order to overcome some of the problems inherent to the existing models.

Abstract
The scheduling problem is considered in complexity theory as a NP-hard combinatorial optimization problem. Meta-heuristics proved to be very useful in the resolution of this class of problems. However, these techniques require parameter tuning which is a very hard task to perform. A Case-based Reasoning module is proposed 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.