Robot-Assisted After-Process Progress-Monitoring System Based on BIM and Computer Vision

Haiou Liao; Bangzhen Huang; Kewei Dong; Zhenzhong Jia; Jing Wu

10.1109/ROBIO58561.2023.10355015

2023-12-04

International Conference on Robotics and Biomimetics

979-8-3503-2571-3

2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)

1-6

2023-12-4--2023-12-9

泰国

Progress monitoring is crucial for the construction industry. It directly impacts the construction period and affects project cost and quality. A lot of previous research focused on in-process progress monitoring. They compared the point cloud of the main structure with the BIM model to check the gap between as-built and as-planned status. This article proposes a BIM-based after-process progress monitoring system based on a visual method. It aims at indoor components after the main structure built. The robot can navigate to the installation sites automatically on a BIM-generated map and check the status of components. We propose a novel and lightweight method for object recognition and estimation of the three-dimensional position of objects relative to BIM coordinate. It is realized by RGB-D camera and deep learning. The semantic and geometric information of BIM is utilized to filter out false recognition of deep learning. The final detection results are compared with BIM to generate a progress-monitoring report. Finally, we build a real robot and check the installation status of four components in a corridor. And all the components are checked successfully.

Deep Learning YOLO Navigation Robot Kinematics Semantics Estimation Feature Extraction

第一 ; 通讯

EI

20240315404317

人工提交

南方科技大学

Haiou Liao,Bangzhen Huang,Kewei Dong,et al. Robot-Assisted After-Process Progress-Monitoring System Based on BIM and Computer Vision[C],2023:1-6.