Rethinking Automation in Construction (ReAC)

ReAC is a research group at Carnegie Mellon’s Computational Design Laboratory investigating new ways of combining artificial intelligence, robotics, and qualitative research methods to support building construction activities. The group’s aim is to advance a humane vision for automation in construction where machines are designed to adaptively support rather than replace or disrupt the work of construction workers. Through qualitative engagements with workers in construction sites and modular factories, and technical research into reinforcement learning and robotics, the group creates “robot in the loop” systems that enhance and interact safely and adaptively with on-site activities. The group comprises faculty, graduate, and undergraduate students in the schools of Architecture, Mechanical Engineering, and the Robotics Institute at Carnegie Mellon University.

The team is led by Professors Daniel Cardoso Llach, Ph.D. (PI, Architecture), and Jean Oh, Ph.D., (Co-PI, Robotics Institute).

Publications

The ReAC group contributes to construction robotics, intelligent robotics, and architectural computing literature. Below is a list of selected publications by the group.

Peer Reviewed Articles

• Wu, Yuning, Emek Erdolu, Jiaying Wei, Jean Oh, and Daniel Cardoso Llach. 2024. “Robot in the Loop: A Human-Centered Approach to Contextualizing AI and Robotics in Construction.” Construction Robotics 9 (1): 1. https://doi.org/10.1007/s41693-024-00144-8.
• Wu, Yuning, Jiaying Wei, Jean Oh, and Daniel Cardoso Llach. 2024. “Towards Human-Centered Construction Robotics: A Reinforcement Learning-Driven Companion Robot for Contextually Assisting Carpentry Workers.” In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 90–97. https://doi.org/10.1109/IROS58592.2024.10802698.
• Stoler, Benjamin, Meghdeep Jana, Soonmin Hwang, and Jean Oh. 2023. “T2FPV: Dataset and Method for Correcting First-Person View Errors in Pedestrian Trajectory Prediction.” In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 4037–44. https://doi.org/10.1109/IROS55552.2023.10341874.
• Wu, Yuning, Jieliang Luo, and Hui Li. 2022. “Learning Dense Reward with Temporal Variant Self-Supervision.” arXiv. https://doi.org/10.48550/arXiv.2205.10431.
• Fang, Zhihao, Yuning Wu, Ammar Hassonjee, Ardavan Bidgoli, and Daniel Cardoso Llach. 2020. “Towards a Distributed, Robotically Assisted Construction Framework.” In Distributed Proximities. Online + Global.

Doctoral Dissertations

• Erdolu, Emek. 2024. “Robotic Technologies and the Reconfiguration of Building Construction Work.” Thesis, Pittsburgh: Carnegie Mellon University. Committee: D. Cardoso Llach, Daragh Byrne, Molly W. Steenson. https://doi.org/10.1184/R1/27304371.v1.
• Yuning Wu. 2024. “A Human-Centered, Reinforcement Learning Driven Robotic Framework For Assisting Construction Workers.” Pittsburgh: Carnegie Mellon University. Advisors: D. Cardoso Llach, Jean Oh; committee members: Rodger Luo (Autodesk) https://kilthub.cmu.edu/articles/thesis/A_Human-Centered_Reinforcement_Learning_Driven_Robotic_Framework_For_Assisting_Construction_Workers/27304317/1.
• Liu, Jingyang. 2024. “Space as Interface: A Computational Framework for Spatial Computing in Robotically-Assisted Construction.” Thesis, Pittsburgh: Carnegie Mellon University. Committee: Josh Bard, Daniel Cardoso Llach, Mayank Goel. https://doi.org/10.1184/R1/26090086.v1.

MS Theses

• Ou, Tingsong. 2023. “Mobile Robot-Assisted Material Handling in Prefabricated Housing Factories.” Thesis, Pittsburgh: Carnegie Mellon University. https://doi.org/10.1184/R1/23960865.v1.
• Liu, Haoyu. 2023. “Towards Contextualized Synthetic Dataset for Construction Site.” Thesis, Pittsburgh: Carnegie Mellon University. https://doi.org/10.1184/R1/23099876.v1.
• Fang, Zhihao. 2021. “Towards Multi-Drone Autonomous Construction via Deep Reinforcement Learning.” Thesis, Pittsburgh: Carnegie Mellon University. https://doi.org/10.1184/R1/14138024.v1.

Presentations

• STS-Hub Berlin; Poster Session, March 13, 2025, Humboldt Universität, Berlin. Poster presentation by PI Daniel Cardoso Llach;
• Institute for Computational Design and Construction, University of Stuttgart, January 29, 2025, Stuttgart. Cluster of excellence lecture by PI Daniel Cardoso Llach;
• TCS Innovation Week; Presidential Fellowship Presentation June 6, 2023, Cornell-Tech Campus, New York City. Presentation by Yuning Wu;
• Talk at the AIA Build PGH Meeting: April 26, 2023, Pittsburgh Convention Center. Presentation by PI Daniel Cardoso Llach;
• Invited talk at the Collective Automation Symposium at New York Institute of Technology; April 26, 2023. Presentation by PI Daniel Cardoso Llach;
• Taubman College of Architecture and Planning Doctoral Symposium Invited guest talk. University of Pennsylvania. March 17, 2023. Discussed ReAC effort among other ongoing and recent research projects. Presentation by PI Daniel Cardoso Llach;
• MFI Technical Exchange, November 10, 2022. Carnegie Mellon University, Pittsburgh, PA. Presentation by PI Daniel Cardoso Llach;
• Manufacturing Futures Initiative Meeting, Pittsburgh, PA, Spring 2022. Presentation by PI Daniel Cardoso Llach;
• Design for Collaborative Robotic Environments symposium at the Center for Design at Northeastern University's College of Arts, Media and Design, alongside Keith Evan Green and Taskin Padir. The panel was convened and moderated by Kristian Kloeckl and introduced by Paolo Ciuccareli. April 21, 2022. Presentation by PI Daniel Cardoso Llach.
• Manufacturing Futures Initiative Meeting, Pittsburgh, PA, Spring 2022. Presentation by PI Daniel Cardoso Llach;
• Association for Computer Aided Design in Architecture, ACADIA, Virtual, 2020. Towards a Distributed, Robotically Assisted Construction Framework. In Distributed Proximities. Presentation by team member Ardavan Bidgoli.

Team

• Daniel Cardoso Llach, Ph.D., Associate Professor, School of Architecture, Carnegie Mellon University (PI);
• Jean Oh, Ph.D., Associate Research Professor, Robotics Institute, Carnegie Mellon University (Co-PI);

Graduate Students (including alumni)

• Yuning Wu, Ph.D. 2024, Computational Design / M.S., Machine Learning;
• Emek Erdolu, Ph.D. 2024, School of Architecture, Computational Design;
• Jiaying Wei, Ph.D. Candidate, School of Architecture, Computational Design;
• Abhishek Singh, Masters of Information Systems Candidate, School of Engineering;
• Yuchen Liu, M.S. Candidate, School of Architecture, Computational Design.
• Zhihao Fang, M.S. 2022, Computational Design.
• Ardavan Bidgoli, Ph.D. 2023, Computational Design.
• Ammar Hassonjee, B.Arch. Student.
• Willa Yang M.S. Computational Design 2023.
• Yanwen Dong, M.S. Computational Design 2023.

Faculty Collaborators

• Dina El Zanfaly, Assistant Professor, School of Design, Carnegie Mellon University

Industry Partners

• PJ Dick
• Module

Sponsors

The ReAC group gratefully acknowledges material support from the Manufacturing Futures Institute, the Pennsylvania Agency for Economic Development, Google, and Autodesk.