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Industrial Robots are designed for tasks such as grasping, welding or painting in where working conditions are well settled. However, if the working conditions change, those robots may not be able to work properly. So, robots require sensorbased control to perform complex operations and to react to changes in the environment. The achievement of such complex applications needs the integration of several research areas in vision and control such as visual matching, visual tracking and visual servoing (Petersson et al. 2002). Information about the actual system and its environment can be obtained from a great variety of sensors. Vision is probably the sensor that provides the greatest and richest sensing information but the processing of such information becomes complicated. Nevertheless, computer vision has been improved a lot in the last years and it is being frequently used in robotics systems, although serious limitations appear in real time applications due to the time necessary for image processing. The use of computer vision as a feedback transducer strongly affects the closed loop dynamics of the overall system. Latency is the most significant dynamic characteristic of vision transducers and it has many sources, including transport delay of pixels from the camera to vision system, image processing algorithms, control algorithms and communications with the robot. This delay can cause instability in visual closed loop systems. To achieve fast response and high control accuracy the design of a specific visual feedback controller is required. Visual servoing is the result of merging several techniques in different fields including image processing, kinematics, dynamics, control theory and real time computing. The task in visual servoing is to control a robot to manipulate its environment with the help of vision as a feedback sensor. An excellent overview of the main issues in visual servoing is given in (Nelson & Papanikolopoulos, 1998). In this work we present a complete form of designing visual servoing controllers for robotic systems built over a modular conception. The designing method is particularly applied to industrial manipulators equipped with a camera mounted on its end effector, known as eye in hand configuration. The modular conception means that the overall system is composed of a set of independent modules, or subsystems, that are put together, configuring a modular system. In this kind of systems any module can be replaced by other one with the same functionality and the visual controller computation procedure will not change. The goal of any visual servoing

Designing and Building Controllers for 3D Visual Servoing Applications under a Modular Scheme