Uncalibrated image-based position-force adaptive visual servoing for constrained robots under dynamic friction uncertainties

Visual servoing of constrained dynamical robots has not yet met a formal treatment. Also, notices that due technological constraints, this task is done slowly at velocity reversals, thus dynamic friction arises, which complicates even more the problem. In this paper, a new adaptive scheme for visual servoing of constrained robots subject to dynamic friction is proposed. An image-based control is introduced to produce simultaneous convergence of the constrained visual position and the contact force between the end-effector and the constraint surface. Camera and robot parameters are considered uncertain. This new 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 camera, encoder and force sensor signals. Simulation results are presented and show that image errors and force errors converge despite uncertainties of friction model.