Probabilistic approach for object bin picking approximated by cylinders

Abstract

This paper proposes a method for bin-picking for objects without assuming the precise geometrical model of objects. We consider the case where the shape of objects are not uniform but are similarly approximated by cylinders. By using the point cloud of a single object, we extract the probabilistic properties with respect to the difference between an object and a cylinder and consider applying the probabilistic properties to the pick-and-place motion planner of an object stacked on a table. By using the probabilistic properties, we can also realize the contact state where a finger maintain contact with the target object while avoiding contact with other objects. We further consider approximating the region occupied by fingers by a rectangular parallelepiped. The pick-and-place motion is planned by using a set of regions in combination with the probabilistic properties. Finally, the effectiveness of the proposed method is confirmed by some numerical examples and experimental result.