Assembly task execution using visual 3D surface reconstruction: An integrated approach to parts mating

This paper is focused on assembly tasks executed by an industrial robotic manipulator in the presence of uncertainties. The goal is to achieve higher levels of autonomy and flexibility of robotic systems in the execution of such tasks. In particular, as a well-established paradigm of assembly tasks, a Peg-in-Hole task has been considered, where the pose of the target object with respect to the robot is known with uncertainties far larger than the task tolerance, e.g., due to manual positioning of the object in the workcell. The proposed approach is based on the reconstruction of the object surface by means of a number of point clouds provided by a depth sensor. The reconstruction is then compared with a known CAD model of the surface, in order to localize the position and tilt of the holes. Finally, the peg insertion is performed in two steps: a search phase, in which the peg tip gently slides on the surface following a trajectory described by Lissajous functions, and a mechanical coupling phase, in which a compliant behavior is imposed to the peg. Experiments on a collaborative manipulator confirm that the proposed approach allows to achieve a better degree of autonomy and flexibility for a class of robotic tasks in partially structured environments.