Grasping unknown novel objects from single view using octant analysis

Abstract

Octant analysis, when combined with properties of the multivariate central limit theorem and multivariate normal distribution, allows finding a reasonable grasping point on an unknown novel object possible. This thesis’s original contribution is the ability to find progressively improving grasp points in a poor and/or sparse point cloud. It is shown how octant analysis was implemented using common consumer grade electronics to demonstrate the applicability to home and office robotics. Tests were carried out on three novel objects in multiple poses to determine the algorithm’s consistency and effectiveness at finding a grasp point on those objects. Results from the experiments bolster the idea that the application of octant analysis to the grasping point problem seems promising and deserving of further investigation. Other applications of the technique are also briefly considered.