Future of Construction: Build Faster, Better, Safer - Together with Robots

May 23, 8:30 AM - 12:30 PM, Philadelphia, United States


The $10 trillion global construction industry has traditionally been a labor-intensive industry, yet it stands to benefit from autonomous robots that promise to deliver construction work that is more accurate and efficient compared to manual or conventional methods. However, the integration of automation and robotic technology into the construction workplace is faced with significant barriers including high cost of entry, safety concerns, inadequate training and knowledge about robotics, and poor performance of robots in dynamic, cluttered and unpredictable environments such as construction sites.

To tackle these challenging issues, this workshop aims to facilitate discussion on technology that will enable advanced robotics for future construction workplaces with an emphasis on robust perception and navigation methods, learning-based task and motion planning, and safety-focused robot-worker interactions. In line with the ICRA 2022 Future of Work theme, this workshop will provide a venue for academics and industry practitioners to create a vision for robotics in construction work and ensure equitable participation in planning for the future of construction workplaces. The half-day workshop will feature presentations by distinguished speakers from both industry and academia as well as interactive activities in the form of poster sessions, debates, and guided group discussions.

The workshop will be held as a hybrid event, with in-person activities as well as a synchronous Zoom session. In-person ICRA attendees who would like to participate in the workshop will be required to register for ICRA with the workshop access option. Remote registration for the conference and workshops is free. More details about the registration fees are available on the ICRA website.

(Virtual attendees) Join us using the following Zoom link:


Workshop Papers

This workshop will solicit contributed papers in the form of extended abstracts (no longer than 4 pages in ICRA paper format, including references) from researchers that are working in construction robotics or closely related fields. The accepted contributed papers will be made publicly available on the workshop website. In addition, the authors of contributed papers will be invited to present their research at the poster session during the workshop. Workshop papers are encouraged and prioritized to be submission of new ideas. A workshop paper submission may be based on a prior publication; however, it cannot take the form of an existing paper that is published or under review. If accepted, workshop papers will also receive a DOI through The International Association for Automation and Robotics in Construction (IAARC) and be made available through the IAARC website.

Submissions can be made through this Google Form, where the paper can be uploaded in PDF format. Authors are encouraged to also submit a 3-minute video presentation of their paper which will be archived in this website. Due to the hybrid nature of the workshop this year, we will also accept submissions from authors who plan to present their work virtually. Questions regarding the paper submission should be directed to chenjingdao@cse.msstate.edu.

Camera-ready paper submissions can be made through this Google Form.

Paper Submission Deadline: May 2 May 9, 5PM Eastern Time

Paper Acceptance Notification: May 9 May 13, 5PM Eastern Time

Camera Ready Paper Deadline: May 16 May 20, 5PM Eastern Time

The topics of interest include, but are not limited to, the following:

  • Safe human-robot collaboration in construction tasks
  • Manipulation, path planning, navigation in dynamic and cluttered environments
  • Robust perception algorithms in cluttered and unstructured environments
  • Collaborative automation technology for heavy construction equipment
  • Automation in construction logistics
  • Wearable robotics / exoskeleton for construction workers
  • Drone technology for construction applications

Best paper awards

Submitted papers will be considered for the best paper awards based on technical merit, originality, and potential impact on the field. The best paper awards come with $1000 in total cash prizes generously sponsored by HILTI (First place: $500, Second place $300, Third place $200). Winners will be announced along with the HILTI Challenge winners during the day of the workshop.

1st prize: AGPNet - Autonomous Grading Policy Network
Chana Ross, Yakov Miron, Yuval Goldfracht, Dotan Di Castro

2nd prize: A Computational Framework For Robotic Quality Assessment and Management In Construction
Jingyang Liu, Yumeng Zhuang, Joshua Bard

3rd prize: Towards the autonomous underwater construction of cement block structures with free-floating robots
Samuel Lensgraf, Amy Sniffen, Alberto Quattrini Li, Devin Balkcom


Exoskeletons in construction and their role in the Future of Work
Sean T. Bennett, Peter G. Adamczyk, Fei Dai, Dharmaraj Veeramani, Michael Wehner, and Zhenhua Zhu
Vision-based Automated Flagging System in Construction
Wei Han and Zhenhua Zhu
Towards the autonomous underwater construction of cement block structures with free-floating robots
Samuel Lensgraf, Amy Sniffen, Alberto Quattrini Li, and Devin Balkcom
TeleLayering: Teleoperated Construction 3D Printing Using Multimodal Feedback for Extraterrestrial and Terrestrial Construction
Ali Kazemian, Hunter Gilbert, Yimin Zhu, Michael R. Fiske, and Natalia Alexandrov
Autonomous Excavator System with Real-World Deployment
Liangjun Zhang, Xibin Song, Liyang Wang, Lingfeng Qian, Tianrui Guan, Zhenpeng He, Zhixian Ye, Ruitao Song, Haodong Ding, and Dinesh Manocha
Upper extremity exoskeletons in construction, a field-based study
Sean T. Bennett, Peter G. Adamczyk, Fei Dai, Dharmaraj Veeramani, Michael Wehner, and Zhenhua Zhu
Projector-Guided Non-Holonomic Mobile 3D Printing
Xuchu Xu, Ziteng Wang, and Chen Feng
Sharing Construction Safety Inspection Experiences and Site-Specific Knowledge through XR-Augmented Visual Assistance
Pengkun Liu, Jinding Xing, Ruoxin Xiong, and Pingbo Tang


Accurate matching between BIM-rendered and real-world images
Houhao Liang and Justin K.W.Yeoh
Low-cost Thermal Mapping for Concrete Heat Monitoring
Alex Junho Lee, Younggun Cho, and Hyun Myung
A Computational Framework For Robotic Quality Assessment and Management In Construction
Jingyang Liu, Yumeng Zhuang, and Joshua Bard
Continuous-Time vs. Discrete-Time Vision-based SLAM: A Comparative Study
Giovanni Cioffi, Titus Cieslewski, and Davide Scaramuzza
Automated Productivity Estimation of Masonry Work using a Deep Learning Approach and Wearable Motion Sensors
Kinam Kim and Yong K. Cho
EASEEbot: A Robotic Envelope Assessment for Energy Efficiency
Guanbo Chen, Beyza Kiper, Xuchu Xu, Bilal Sher, Semiha Ergan, and Chen Feng


AGPNet - Autonomous Grading Policy Network
Chana Ross, Yakov Miron, Yuval Goldfracht, and Dotan Di Castro
A Reinforcement Learning Based Approach for Conducting Multiple Tasks using Robots in Virtual Construction Environments
Weijia Cai and Zhengbo Zou
Deep Reinforcement Learning-based Construction Robots Collaboration for Sequential Tasks
Lei Huang and Zhengbo Zou

Human Robot Collaboration

Exploiting the Power of Human-Robot Collaboration: Coupling and Scale Effects in Bricklaying
Jia-Rui Lin and Minghui Wu
Towards a Collaborative Future in Construction Robotics: A Human-centered Study in a Multi-user Immersive Operation and Communication System for Excavation
Di Liu, Youngjib Ham, Jeonghee Kim, and Hangue Park
The effect of challenging work environment on human-robot interaction and cognitive load during teleoperation: a case study of teleoperated excavator in a virtual experiment
Jin Sol Lee and Youngjib Ham

HILTI Challenge

This workshop will involve a Simultaneous Localization and Mapping (SLAM) competition organized by HILTI. The competition will focus on the SLAM problem in environments with challenging features such as changing light conditions, difficult geometries, and fast movements. The competition submission deadline is May 16 and the winners will be announced on May 23 (during the workshop). The challenge website may be accessed here.

1st place: Wildcat (CSIRO)
Milad Ramezani, Gavin Catt, Kasra Khosoussi, Fred Pauling, Peyman Moghadam

2nd place: MC2MAP Algorithm (V&R)
Frank Neuhaus, Tilman Koß

3rd place: Towards Efficient and Accurate 3D Dense SLAM Technology (MARS Lab)
Wei Xu, Zheng Liu, Chongjian Yuan, Xiyuan Liu, Fu Zhang



Prof. Dinesh Manocha

University of Maryland

Prof. Manocha is currently the Paul Chrisman Iribe Chair of Computer Science and Electrical and Computer Engineering at the University of Maryland at College Park. He co-leads a major research group with more than 20 members on geometric and simulation algorithms with applications to computer graphics, robotics and virtual environments. His recent research include the investigation of terrain mapping, multimodal perception and hierarchical task and motion planning for autonomous excavator navigation in unstructured environments.


Prof. Michael Milford

Queensland University of Technology

Prof. Milford currently holds the positions of Director of the QUT Centre for Robotics (acting), Professor at the Queensland University of Technology. He conducts interdisciplinary research at the boundary between robotics, neuroscience and computer vision and is a multi-award winning educational entrepreneur. His research models the neural mechanisms in the brain underlying tasks like navigation and perception to develop new technologies in challenging application domains such as all-weather, anytime positioning for autonomous vehicles. His recent projects include translational research into industrial applications such as delivering centimeter-accurate positioning for automation of underground mining robots.


Noah Ready-Campbell

Built Robotics

Noah is the founder and CEO of Built Robotics, a company with a mission to build the robots that build the world. He founded the company in 2016, and has raised over $48 million from leading Silicon Valley investors including Founders Fund, NEA and Next47. Noah began his career at Google, and he studied business and engineering at the University of Pennsylvania. Built Robotics transforms heavy equipment into autonomous robots for the $1 trillion earthmoving industry.


Dr. Martin Karlsson

Built Robotics

Martin Karlsson is a Senior Robotics Engineer at Built Robotics, a company building autonomous tools for heavy equipment. Martin earned his Ph.D. in robotics from Lund University, where his focus was on motion and force control. After receiving his doctorate, Martin continued advanced research in robotics at Lund. His work at Built touches all aspects of autonomous operation, and he has been responsible for improving the motion and perception capabilities of the robots in real-world construction applications.


Dr. Bharath Sankaran

Scaled Robotics

Dr. Bharath Sankaran is the CTO and co-founder of Scaled Robotics, a Barcelona-based construction robotics company that leverages the state-of-the-art in machine learning, artificial intelligence, and robotics to build new tools that can track, analyze, and optimize construction processes. Since its founding in 2017, Scaled Robotics has grown into a diverse organization that brings new and unique perspectives to the problems facing the construction industry. Dr. Sankaran received his PhD from the University of Southern California, and has worked at the Max Planck Institute for Intelligent Systems, the GRASP Lab at UPenn, the Robotics Institute at CMU, and the Space Systems Lab at the University of Maryland. At Scaled Robotics, he leads a team that has developed pioneering solutions for complex 3D active perception and control problems in highly unstructured construction environments.


Prof. Hyun Myung

Korea Advanced Institute of Science and Technology

Prof. Myung is a Professor at the School of Electrical Engineering at KAIST and is the Chief of the KAIST Robotics Program. His research interests include autonomous robot navigation, SLAM (simultaneous localization and mapping), SHM (structural health monitoring), machine learning, AI, and swarm robots. Prof. Myung leads the Urban Robotics Lab at KAIST and has successfully developed multiple innovative robot platforms such as wall-climbing aerial robots, mole-like digging robots, and bird-like biped robots for rough terrain.


08:30 AM

Workshop introduction and opening remarks

Dr. Yong K. Cho
08:40 AM

Invited speaker: academic

Dr. Dinesh Manocha
AES: Autonomous Excavator System for Material Loading Tasks
09:00 AM

Invited speaker: academic

Dr. Michael Milford
Towards Construction Robotics: Scene Understanding, Positioning, and Insights from Other Domains
09:20 AM

Invited speaker: industry

Dr. Bharath Sankaran (Scaled Robotics)
Future of Construction: ML and AI for construction process control
09:40 AM

Invited speaker: academic

Dr. Hyun Myung
Autonomous Navigation and Inspection for Smart Cities
10:00 AM

Invited speaker: industry

Noah Ready-Campbell (Built Robotics)
Martin Karlsson (Built Robotics)
Economic Excavator Control Design
10:20 AM

Coffee break

10:30 AM

Panel Q&A

10:50 AM

HILTI challenge results | Poster session

11:35 AM

Team debate

Initial audience poll (3 min)
Introductions (5 min = 2 persons x 2.5 min each)
Opening arguments (10 min = 4 persons x 2.5 min each)
Moderated discussion between debaters, audience Q&A (25 min)
Closing remarks (5 min = 2 persons x 2.5 min each)
Final audience poll (2 min)

Opinion A: In the future, construction will likely be carried out by autonomous robots with minimal human workers.
Team A: Michael Milford, Noah Ready-Campbell, Martin Karlsson

Opinion B: In the future, construction will likely be carried out by human-robot collaborative systems with many human workers.
Team B: Bharath Sankaran, Dinesh Manocha, Kris Morin

Initial poll

Final poll

12:25 PM

Closing remarks

12:30 PM

End of workshop



Dr. Yong K. Cho

Georgia Institute of Technology


Dr. Jingdao Chen

Mississippi State University

(Primary Contact Person) chenjingdao@cse.msstate.edu


Dr. Inbae Jeong

North Dakota State University


Dr. Chen Feng

New York University


Dr. Liangjun Zhang

Baidu Research


This workshop is made possible thanks to the generous sponsorship of the following organizations: