Task-space control of robotic manipulators relies on inverse kinematic algorithms with singularity handling capabilities. Damped least-squares inverse kinematics gives well-behaved joint solutions even in the neighbourhood of singular configurations; this is obtained by weighting tracking accuracy against the feasibility of the resulting joint motion. In this paper it is shown how to use the weighted damped least-squares inverse kinematics when the task to be executed requires a high accuracy in assigned task-space components, while allowing a lower tracking performance in the other directions. The technique is first analysed in simulation and is then applied in experiments to control an industrial manipulator.
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