TY - GEN
T1 - BIM-DRIVEN MISSION PLANNING AND NAVIGATION FOR AUTOMATIC INDOOR CONSTRUCTION PROGRESS DETECTION USING ROBOTIC GROUND PLATFORM
AU - Ibrahim, Amir
AU - Sabet, Ali
AU - Golparvar-Fard, Mani
N1 - Publisher Copyright:
© European Council on Computing in Construction (EC3).
PY - 2019
Y1 - 2019
N2 - 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 in the narrow cluttered indoor space. In this paper we present a novel pipeline for 4D BIM-driven mapping of the as-built state of indoor construction site. 2D Light Detection and Ranging (LiDAR) sensors are mounted on an Unmanned Ground Vehicle (UGV) for Simultaneous Localization and Mapping (SLAM). 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 UGVs.
AB - 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 in the narrow cluttered indoor space. In this paper we present a novel pipeline for 4D BIM-driven mapping of the as-built state of indoor construction site. 2D Light Detection and Ranging (LiDAR) sensors are mounted on an Unmanned Ground Vehicle (UGV) for Simultaneous Localization and Mapping (SLAM). 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 UGVs.
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U2 - 10.35490/EC3.2019.195
DO - 10.35490/EC3.2019.195
M3 - Conference contribution
AN - SCOPUS:85177179441
SN - 9781910963371
T3 - Proceedings of the European Conference on Computing in Construction
SP - 182
EP - 189
BT - Proceedings of the 2019 European Conference on Computing in Construction
A2 - O'Donnell, James
A2 - Chassiakos, Athanasios
A2 - Rovas, Dimitrios
A2 - Hall, Daniel
PB - European Council on Computing in Construction (EC3)
T2 - European Conference on Computing in Construction, EC3 2019
Y2 - 10 July 2019 through 12 July 2019
ER -