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This paper presents a new dual quaternion-based formulation for pose-basedvisual servoing. Extending our previous work on local contact moment (LoCoMo)based grasp planning, we demonstrate grasping of arbitrarily moving objects in3D space. Instead of using the conventional axis-angle parameterization, dualquaternions allow designing the visual servoing task in a more compact mannerand provide robustness to manipulator singularities. Given an object pointcloud, LoCoMo generates a ranked list of grasp and pre-grasp poses, which areused as desired poses for visual servoing. Whenever the object moves (trackedby visual marker tracking), the desired pose updates automatically. For this,capitalising on the dual quaternion spatial distance error, we propose adynamic grasp re-ranking metric to select the best feasible grasp for themoving object. This allows the robot to readily track and grasp arbitrarilymoving objects. In addition, we also explore the robot null-space with ourcontroller to avoid joint limits so as to achieve smooth trajectories whilefollowing moving objects. We evaluate the performance of the proposed visualservoing by conducting simulation experiments of grasping various objects usinga 7-axis robot fitted with a 2-finger gripper. Obtained results demonstrate theefficiency of our proposed visual servoing.

Dual Quaternion-Based Visual Servoing for Grasping Moving Objects