In this paper, the design of a position tracking control scheme for an industrial robot manipulator is considered. The design is based on the normalized left coprime factors robust stabilization approach. By coupling this H/sub /spl infin// synthesis to a sequential quadratic programming optimization procedure, a systematic design method is developed optimizing the performance of the controller. Further, the role of the nominal model for the design is explored. The control scheme is successfully implemented and tested on a real industrial robot manipulator. The computed controller worked immediately in the first experiment without any further tuning and showed excellent robust performance.

Presents a method for robot modelling called "double dynamic modelling". This method is based on an improvement of the classic dynamic model which takes into account the gear trains included in the robot axes, especially the gear yields and the direction of power transmission in the gears. According to this direction the dynamic model becomes different. Experimental results on a biped robot are given, which show the improved accuracy of the new dynamic model and better performances of the computed-torque control implemented in the biped robot and based on this model.>

In this paper, we present a model-based vision system using a CCD camera mounted on the end-effector of an industrial robot. We describe an autonomous monocular vision system which is used as a feedback signal to control the position and orientation of the manipulator with respect to a dynamic object part of a 3D scene. Without any previous knowledge of the part's placement or motion, this visual feedback would allow a robot to track a pattern in real time. Applications for such a vision-guided robot include 3D object recognition, by extracting 2D image features and rebuilding 3D features. This is performed via rigidity constraint and search comparison in model database geometric inference. Kinematic redundancy is used for general solution of joint velocity represented by the generalized inverse of Jacobian matrix. The problem of redundancy utilization can generally be formulated in the framework of tasks with the order of priority. We present a visual servoing scheme using the task function approach in term of 6 degrees of freedom of robot's gripper regulation. Redundancy theory allows to control position and orientation of the end-effector of an industrial robot in less than 80 ms of cycle time.>