Momentum Transfer from Preshape to Grasping

2014-08-01
Ozyer, Baris
Erkmen, İsmet
Erkmen, Aydan Müşerref
A fully immersed object, suspended in water can be rotated from distance by a preshaped robot hand approaching and closing upon the object prior to contacting it. Momentum transfer from robot fingers closing into a grasp, to the fluid medium particles, and from these particles to the object surface generates the motion tendencies of that object in terms of rotational and translational displacements. In this paper, we propose the novel concept of a controller that determines either: 1) given initial position and orientation of a robot hand, what preshape is suitable for generating a desired momentum distribution on the surface of a given object in order to trigger a desired rotation in a desired direction when approaching with this preshaped hand; or 2) given a predetermined hand preshape, what initial position, orientation and hand aperture are suitable to generate a desired rotation upon approach and, without causing the retroceeding of the object. The desired object motion generated from distance by the approach of a hand preshape is to be used seamlessly for the subsequent manipulation of the object upon grasp. Towards this end, we propose in our work, a new model based on computational fluid dynamics, for determining the continuity in momentum transfer from robot hand fingers to the fluid medium, and to the object, until landing on that immersed object. Our experimental results demonstrate how different hand preshapes initiated from different locations in the medium surrounding an object of different cross sections suspended in equilibrium in the fluid, affects its motion tendencies in terms of rotation and translation. Our further contribution, in this paper, includes the modelling of robot fingers and object as fluidic elements which rigidity can be relaxed to induce compliance.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS

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Citation Formats
B. Ozyer, İ. Erkmen, and A. M. Erkmen, “Momentum Transfer from Preshape to Grasping,” JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, pp. 173–191, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47556.