Preparatory object reorientation for task-oriented grasping

In the IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016.

Title: Preparatory Object Reorientation for Task-Oriented Grasping
Authors: Anh Nguyen, Dimitrios Kanoulas, Darwin G. Caldwell, and Nikos G. Tsagarakis

Abstract: This paper describes a new task-oriented grasping
method to reorient a rigid object to its nominal pose, which is
defined as the configuration that it needs to be grasped from,
in order to successfully execute a particular manipulation task.
Our method combines two key insights: (1) a visual 6 Degreeof-Freedom
(DoF) pose estimation technique based on 2D-3D
point correspondences is used to estimate the object pose in
real-time and (2) the rigid transformation from the current to
the nominal pose is computed online and the object is reoriented
over a sequence of steps. The outcome of this work is a novel
method that can be effectively used in the preparatory phase of
a manipulation task, to permit a robot to start from arbitrary
object placements and configure the manipulated objects to the
nominal pose, as required for the execution of a subsequent
task. We experimentally demonstrate the effectiveness of our
approach on a full-size humanoid robot (WALK-MAN) using
different objects with various pose settings under real-time
constraints