{"title":"Mapping Walls of Indoor Environment Using Moving RGB-D Sensor","authors":"Ismail Rusli, B. Trilaksono, W. Adiprawita","doi":"10.1109/ICOICT.2018.8528805","DOIUrl":null,"url":null,"abstract":"Inferring walls configuration of indoor environment could help robot “understand” the environment better. This allows the robot to execute a task that involves inter-room navigation, such as picking an object in the kitchen. In this paper, we present a method to inferring walls configuration from a moving RGB-D sensor. Our goal is to combine a simple wall configuration model and fast wall detection method in order to get a system that works online, is real-time, and does not need a Manhattan World assumption. We tested our preliminary work, i.e. wall detection and measurement from moving RGB-D sensor, with MIT Stata Center Dataset. The performance of our method is reported in terms of accuracy and speed of execution.","PeriodicalId":266335,"journal":{"name":"2018 6th International Conference on Information and Communication Technology (ICoICT)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 6th International Conference on Information and Communication Technology (ICoICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOICT.2018.8528805","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Inferring walls configuration of indoor environment could help robot “understand” the environment better. This allows the robot to execute a task that involves inter-room navigation, such as picking an object in the kitchen. In this paper, we present a method to inferring walls configuration from a moving RGB-D sensor. Our goal is to combine a simple wall configuration model and fast wall detection method in order to get a system that works online, is real-time, and does not need a Manhattan World assumption. We tested our preliminary work, i.e. wall detection and measurement from moving RGB-D sensor, with MIT Stata Center Dataset. The performance of our method is reported in terms of accuracy and speed of execution.
推断室内环境的墙体配置可以帮助机器人更好地“理解”环境。这使得机器人可以执行包括房间间导航的任务,比如在厨房里挑选一个物体。在本文中,我们提出了一种从移动的RGB-D传感器推断壁面结构的方法。我们的目标是结合一个简单的墙配置模型和快速的墙检测方法,以获得一个在线工作的系统,是实时的,不需要曼哈顿世界的假设。我们使用MIT Stata Center数据集测试了我们的初步工作,即移动RGB-D传感器的墙壁检测和测量。我们的方法在准确性和执行速度方面的性能得到了报道。