Abstract

Abstract
In the present industrial manufacturing scenario it is required that work cells would be easier to manipulate. Therefore there is a demand for simple orchestration techniques of different industrial devices, such as vision systems, cameras, sensors, PLCs, pocket-PCs. This paper meets this need by implementing a dynamic graphical user interface (GUI) based on the StateCharts concept. The paper describes the choices made in the construction, namely regarding the handling of hierarchy and discusses their implications in the effectiveness of the GUI. Some tests made with the software that resulted from this paper also show that the introduction of a GUI that represents event-based systems, like StateCharts, could be a precise and simple tool for the construction of complex industrial cells by non-expert users.

Abstract
A maximin multiobjective particle swarm optimization algorithm variant is presented, in the context of parallel robotic manipulator design. The choice of a particular structural configuration and its dimensioning is a central issue to the performance of these manipulators. A solution to the dimensioning problem, normally involves the definition of performance criteria as part of an optimization process. In this paper the kinematic design of a 6-dof parallel robotic manipulator is analyzed. Two dynamic performance criteria are formulated and non-dominated optimal solutions are found through a multi-objective particle swarm optimization algorithm. Preliminary simulation results are presented.

Abstract
The particle swarm optimization algorithm is proposed as a tool to solve the Posicast input command shaping problem. The design technique is addressed, in the context of a simulation teaching experiment, aiming to illustrate second-order system feedforward control. The selected experiment is the well known suspended load or gantry problem, relevant to the crane control. Preliminary simulation results for a quarter-cycle Posicast shaper, designed with the particle swarm algorithm are presented. Illustrating figures extracted from an animation of a gantry example which validate the Posicast design are presented.

Abstract
Despite the benefits of precision agriculture and precision viticulture production systems, its adoption rate in the Portuguese Douro Demarcated Region remains low. One of the most demanding tasks in wine making is harvesting. Even for humans, the environment makes grape detection difficult, especially when the grapes and leaves have a similar color, which is generally the case for white grapes. In this paper, we propose a system for the detection and location, in the natural environment, of bunches of grapes in color images. The system is also able to distinguish between white and red grapes, at the same time, it calculates the location of the bunch stem. The proposed system achieved 97% and 91% correct classifications for red and white grapes, respectively.

Abstract
The rate of adoption of Precision Agriculture and Precision Viticulture production systems in the Douro Demarcated Region remains low. We believe that one way to raise it is to address challenging real-world problems whose solution offers a clear benefit to the viticulturist. For example, one of the most demanding tasks in wine making is harvesting. Even for humans, the detection of grapes in their natural environment is not always easy. White grapes are particularly difficult to detect, since their color is similar to that of the leafs. Here we present a low cost system for the detection of white grapes in natural environment color images. The system also calculates the probable location of the bunch stem and achieves 91% of correct classifications.