Visual Servoing Based on a Task Function Approach

Kecent advances in vision sensors technology and image processing authorize to hope that the use of vision data directly into the control loop of a robot is no more an utopic way. Commonly, the general approach in robot vision is the following: processing vision data into the frame linked to the sensor, converting data into the frame linked to the scene by mean of inverse calibration matrix, computing, with respect to the robot task, the control vector of the robot into the frame linked to the scene, controlling the robot by using the inverse kinematic model. This scheme works in open loop with respect to vision data and cannot take into account inaccuracies and uncertainties occurlng during the processing. Such am approach needs to perfectly overcome the constraints of the problem: geometry of the sensor (for example, in a stereovision method), the model of the environment and the model of the robot. In some cases, this approach is the only one possible but, in many cases, an alternative way consists to specify the robot task in terms of control directly into the sensor frame. This approach is often referred as visual servoing [8] , [3] or sensor based control [2]; in this case, a closed loop can be really performed from the vision data and allows to compensate for the perturbations by a robust control scheme. The work described in this paper deals with such an approachusing a mobile vision sensor mounted on the end effector of a robot manipulator. It is characterized by two main points:the use of vision sensor as local sensor providing relatively poor instantaneous information but at a rate consistent with the bandwith of the robot controller and the exploitation of the vision data into a robust control scheme based on a task function approach [7]. 1 T h e F r a m e w o r k of S e n s o r b a s e d C o n t r o l 1 .1 Background We are interested in this paper in the design of control systems which work in closed loop with regard to the environment , with the point of view of au tomat ic control.This means that sensors exclusively devoted to supplying of symbolic information will not be considered, and that only high da ta rate sensors are used. This excludes, for example,