Modeling of everyday objects for semantic grasp

The 23rd IEEE International Symposium on Robot and Human Interactive Communication Pub Date : 2014-10-20 DOI:10.1109/ROMAN.2014.6926343

Y. Shiraki, K. Nagata, N. Yamanobe, Akira Nakamura, K. Harada, D. Sato, D. Nenchev

{"title":"Modeling of everyday objects for semantic grasp","authors":"Y. Shiraki, K. Nagata, N. Yamanobe, Akira Nakamura, K. Harada, D. Sato, D. Nenchev","doi":"10.1109/ROMAN.2014.6926343","DOIUrl":null,"url":null,"abstract":"This paper presents a knowledge model of everyday objects for semantic grasp. This model is intended for extracting the grasp areas of everyday objects and approach directions for grasping when the 3D point cloud data and the intended purpose are given. Parts that make up everyday objects have functions related to their manipulation. We therefore represent everyday objects in terms of connected parts of functional units. This knowledge model describes the structure of everyday objects and information on their manipulation. The structure of an everyday object describes component parts of the object in terms of simple shape primitives to provide geometrical information and describes connections between parts with kinematic attributes. The information on the structure is used to map the manipulation knowledge onto the 3D point cloud data. The manipulation knowledge of the object includes the grasp areas and approach directions for the intended purpose. Fine grasps suitable for the intended task can be generated by performing a grasp planning with consideration for stable grasp and the kinematics of the robot in the grasp areas and approach directions.","PeriodicalId":235810,"journal":{"name":"The 23rd IEEE International Symposium on Robot and Human Interactive Communication","volume":"171 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 23rd IEEE International Symposium on Robot and Human Interactive Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROMAN.2014.6926343","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 16

Abstract

This paper presents a knowledge model of everyday objects for semantic grasp. This model is intended for extracting the grasp areas of everyday objects and approach directions for grasping when the 3D point cloud data and the intended purpose are given. Parts that make up everyday objects have functions related to their manipulation. We therefore represent everyday objects in terms of connected parts of functional units. This knowledge model describes the structure of everyday objects and information on their manipulation. The structure of an everyday object describes component parts of the object in terms of simple shape primitives to provide geometrical information and describes connections between parts with kinematic attributes. The information on the structure is used to map the manipulation knowledge onto the 3D point cloud data. The manipulation knowledge of the object includes the grasp areas and approach directions for the intended purpose. Fine grasps suitable for the intended task can be generated by performing a grasp planning with consideration for stable grasp and the kinematics of the robot in the grasp areas and approach directions.

查看原文本刊更多论文

日常物品的建模以掌握语义

本文提出了一种用于语义把握的日常事物知识模型。该模型用于在给定三维点云数据和预期目的的情况下，提取日常物体的抓取区域，逼近抓取方向。组成日常物品的部件具有与其操作相关的功能。因此，我们用功能单元的连接部分来表示日常物体。这个知识模型描述了日常物品的结构和它们的操作信息。日常物体的结构用简单的形状基元来描述物体的组成部分，以提供几何信息，并用运动学属性来描述部件之间的联系。利用结构上的信息将操作知识映射到三维点云数据上。所述对象的操作知识包括达到预期目的的抓取区域和接近方向。通过考虑稳定抓取和机器人在抓取区域和接近方向上的运动学，进行抓取规划，可以生成适合预定任务的精细抓取。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

The 23rd IEEE International Symposium on Robot and Human Interactive Communication

自引率

0.00%

发文量