Name
Abstract | ||
|---|---|---|
A novel method for object grasping.Unified grasping system capable of answering queries such as What, Where and How.\"What\" is handled by a state-of-the-art object recognition framework.\"Where\" is answered by a manifold modeling-based 6 DoF pose estimation technique.\"How\" is tackled through an ontology-based semantic categorization. In this paper we propose a novel method for object grasping that aims to unify robot vision techniques for efficiently accomplishing the demanding task of autonomous object manipulation. Through ontological concepts, we establish three mutually complementary processes that lead to an integrated grasping system able to answer conjunctive queries such as \"What\", \"Where\" and \"How\"? For each query, the appropriate module provides the necessary output based on ontological formalities. The \"What\" is handled by a state of the art object recognition framework. A novel 6 DoF object pose estimation technique, which entails a bunch-based architecture and a manifold modeling method, answers the \"Where\". Last, \"How\" is addressed by an ontology-based semantic categorization enabling the sufficient mapping between visual stimuli and motor commands. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.eswa.2015.06.039 | Expert Systems with Applications |
Keywords | Field | DocType |
Object grasping,Object recognition,Pose estimation,Ontology-based semantic categorization | Categorization,Ontology,Conjunctive query,Architecture,Computer science,Pose,Artificial intelligence,Machine learning,Manifold,Visual perception,Cognitive neuroscience of visual object recognition | Journal |
Volume | Issue | ISSN |
42 | 21 | 0957-4174 |
Citations | PageRank | References |
0 | 0.34 | 53 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rigas Kouskouridas | 1 | 109 | 7.52 |
| Angelos Amanatiadis | 2 | 87 | 11.71 |
| Savvas A. Chatzichristofis | 3 | 810 | 44.88 |
| Antonios Gasteratos | 4 | 526 | 54.24 |