Visual servoing for constrained robots: a new complete theoretical framework and its experimental validation

The theoretical framework and experimental validation of a new image-based position-force control is presented in this paper. This scheme produces simultaneous convergence of the constrained visual position and the contact force between the end-effector and the constraint surface. Camera, robot and Jacobian parameters are considered uncertain. This approach is based on a new formulation of the orthogonalization principle used in force control, coined here visual orthogonalization principle. This allows, under the framework of passivity, to yield a synergetic scheme that fuses accordingly camera, encoder and force sensor signals. Furthermore, notice that visual servoing contact tasks are characterized by slow motion, and typically with velocity reversals along the constrained surface due actual technological limitations of the camera, thus, important problems of friction at the joint and contact point arise. Therefore, in this paper, compensation of dynamic joint friction and viscous contact friction are also studied. In order to prove the effectiveness of the theoretical scheme, a Linux-RTAI real-time OS experimental system is used to obtain a direct-drive robot manipulator equipped with six axis JR3 force sensor and a CCD commercial digital fixed camera. Results show an excellent performance