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Grasping unknown objects using an Early Cognitive Vision system for general scene understanding
Author(s) -
Marija Popović,
Gert Kootstra,
Jimmy Alison Jørgensen,
Danica Kragić,
Norbert Krüger
Publication year - 2011
Publication title -
2011 ieee/rsj international conference on intelligent robots and systems
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1109/iros.2011.6048619
Subject(s) - reachability , robustness (evolution) , computer science , robot , artificial intelligence , machine learning , perception , stability (learning theory) , theoretical computer science , biochemistry , chemistry , neuroscience , biology , gene
Grasping unknown objects based on real-world visual input is a challenging problem. In this paper, we present an Early Cognitive Vision system that builds a hierarchical representation based on edge and texture information, which is a sparse but powerful description of the scene. Based on this representation we generate edge-based and surface-based grasps. The results show that the method generates successful grasps, that the edge and surface information are complementary, and that the method can deal with more complex scenes. We furthermore present a benchmark for visual-based grasping.© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.EU project eSMCs (IST-FP7-IP-270212)SSF RoS

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