BIM-driven mission planning and navigation for automatic indoor construction progress detection using robotic ground platform

Amir Ibrahim1, Ali Sabet2, Mani Golparvar-Fard1
1 University of Illinois at Urbana Champaign, United States of America
2 University of Waterloo, Canada


DOI: 10.35490/EC3.2019.195
Abstract: Reconstructing a complete and accurate 3D representation of indoor construction scenes is an important step towards automated visual monitoring of construction projects. For fast access to construction’s as-built visual data, construction drones are programmed to autonomously navigate the outdoor space and collect the data. However, due to limited satellite signal indoors, ground rovers provide safer and more reliable autonomous navigation inside the narrow indoor navigable space. In this paper we present a novel pipeline for 4D BIM-driven mapping of the as- built state of indoor construction using 2D Light Detection and Ranging (LiDAR) sensors mounted on an Unmanned Ground Vehicle (UGV). The developed method consists of (1) BIM-driven data collection planning; (2) automatic mission navigation; (3) LiDAR data collection and (4) dynamic obstacle avoidance. Experiments show the applicability of the developed data collection strategy and the improved safety of automatic mission execution using UGV.
Keywords: BIM-Driven Data Collection, LiDAR Data, Unmanned Ground Robot, Automated Data Collection, Indoor Construction
Pages: 182 - 189
Paper:
http://ec-3.org/conf2019/contribution_195_final/