Automated Reverse Engineering of Buildings - Robotics Institute Carnegie Mellon University
Graphical depiction of the Automated Reverse Engineering of Buildings project
Automated Reverse Engineering of Buildings
Project Head: Daniel Huber

Laser scanners have proven to be an effective method for measuring the 3D shape of facilities, such as buildings and process plants. The results of scanning can be used to model the as-built or as-is conditions of a facility, which may be very different from the original design plans. Unfortunately, laser scanners produce data in the form of a set of points (known as a point cloud), but people using the data need higher-level information like the identity, location, and shape of walls, doors, and windows. In practice this high-level information is usually represented as a building information model (BIM). Our research is exploring methods to automatically create BIMs from point clouds and to address specific challenges in representing such “as-built” BIMs. Our modeling work utilizes techniques from the fields of computer vision and machine learning to automatically segment, model, and recognize the core components of a building’s envelope, including walls, floors, ceilings, doors, and windows. Our representation work is addressing problems specific to as-built BIMs. One such problem is the representation of occluded regions. Normally, when a room is scanned, some parts of the walls will be blocked by furniture or other obstructions. When the as-built BIM is created, the modeled walls are extended to fill in these occluded regions. However, the representation makes no distinction between regions that were filled in and regions that were measured directly. A downstream stakeholder may then make poor decisions based on incorrect assumptions about the accuracy of the data in these originally occluded regions.



Currently, we are investigating several different aspects of the problem of automatic reverse engineering of buildings:



This project is funded in part, by the National Science Foundation (CMMI-0856558) and by the Pennsylvania Infrastructure Technology Alliance.

Displaying 6 Publications

2013
Xuehan Xiong, Antonio Adan Oliver, Burcu Akinci, and Daniel Huber
Journal Article, Automation in Construction, Vol. 31, pp. 325 - 337, May, 2013
2011
Antonio Adan Oliver, Xuehan Xiong, Burcu Akinci, and Daniel Huber
Conference Paper, Proceedings of International Symposium on Automation and Robotics in Construction (ISARC '11), June, 2011
Engin Anil, Burcu Akinci, and Daniel Huber
Conference Paper, Proceedings of International Symposium on Automation and Robotics in Construction (ISARC '11), June, 2011
Antonio Adan Oliver and Daniel Huber
Conference Paper, Proceedings of 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), May, 2011
Daniel Huber, Burcu Akinci, Antonio Adan Oliver, Engin Anil, Brian E. Okorn, and Xuehan Xiong
Conference Paper, Proceedings of NSF Engineering Research and Innovation Conference, 2011
2010
Daniel Huber, Burcu Akinci, Pingbo Tang, Antonio Adan Oliver, Brian E. Okorn, and Xuehan Xiong
Conference Paper, Proceedings of 44th Annual Conference on Information Sciences and Systems (CISS '10), March, 2010

current head

current staff

current contact

past head

  • Burcu Akinci

past staff

  • Engin Anil
  • Emiliano Perez Hernandez
  • Antonio Adan Oliver
  • Enrique Valero Rodriguez
  • Siddharth Soundararajan