The vast majority of robots are controlled through the use of encoders that measure joint rotation. But even when encoders with very high levels of accuracy are used, the ability of robots to move to an absolute XYZ position and ABC orientation is limited by deflection, thermal expansion and manufacturing variation. Some applications, such as placement of a disk drive read head, require very higher levels of positioning accuracy that can only be achieved with a very expensive, special purpose robot. This challenge is being addressed with visual servoing technology that uses a vision system to acquire an image that determines the relative positions of the robot end-effector and the target.
“The concept of the hidden robot model is a powerful tool able to analyze the intrinsic properties of some controllers developed by the visual servoing community,” Sébastien Briot concluded. “Adams simulations have played an important role in validating our theoretical work on hidden robot models. The integration of Adams with Simulink through Adams/Controls eliminated the need for us to write complex equations for predicting the dynamics of parallel robots and also provided graphical results that gave us a better understanding of robot behavior.”