Mapping Walls of Indoor Environment Using Moving RGB-D Sensor

被引：0

作者：

Ismail ^{[1
]}

Trilaksono, Bambang Riyanto ^{[1
]}

Adiprawita, Widyawardana ^{[1
]}

机构：

[1] Inst Teknol Bandung, Sch Elect Engn & Informat, Bandung 40123, Indonesia

来源：

2018 6TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY (ICOICT) | 2018年

关键词：

SLAM; semantic mapping; RGB-D sensor; indoor environment; LOCALIZATION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：337 / 342

页数：6

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