The theoretical framework and the experimental validation of a new image-based position-force control for planar robots are 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 the visual jacobian parameters are considered unknown. This approach is based on a new formulation of the orthogonalization principle used in the robot force control, termed the visual orthogonalization principle. This allows, under the framework of passivity, to yield a synergetic closed-loop system that fuses accordingly camera, encoder, and the force sensor signals. Furthermore, due to the technological limitations, it can be noticed that the visual servoing contact tasks are characterized by slow motion, typically with frequent velocity reversals along the constraint surface, thus, important friction problems arise at the joints and the contact points. Therefore, visual compensation of the complex dynamic joint friction and the viscous contact friction are also studied. A Linux real-time operating-system-based experimental system is implemented to visually drive a constrained direct-drive planar robot manipulator, equipped with six-axes JR3 force sensor and a digital fixed camera, thus proving the effectiveness of the proposed scheme.
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