The innovations in the Architecture, Engineering, and Construction (AEC) industry have expanded greatly from carving out doric columns by hand with mathematic precision in 430 BCE to the invention of fully clear photovoltaic glass in 2014. Today, the AEC’s greatest accomplishment is Robotic Construction technology. Robotics can be described as technology that uses human input to automate typically human tasks.
In AEC, robots are able to create large format 3D prints, 3D imaging, cut with precision, and assembly tasks. Discussions on the impact robotics has on the AEC industry have occurred since the concept of robots began in the early 20th century. However, those conversations or articles are usually incredibly vague, such as “Robotics reduce costs” or “Robotics are more efficient.” Typically followed up with an even more vague source and no case studies proving these claims. Although robotics have the potential for advantageous impacts in terms of cost, sustainability, efficiency, safety, and precision, let’s explore and analyze real case studies that address the real-world impacts of robotic technology.
In 2022, Cynthia Brosque and Martin Fischer published the Safety, quality, schedule, and cost impacts of ten construction robots. They document extensively the exploration and comparison between Robotic Technology and Manual Human Construction methods. The study involves 12 projects, 11 contractors, and four countries across Asia, Europe, South America, and the US. Each Contractor is paired with robotic machinery to do similar tasks. Below are summaries of their case studies and outcomes.
Robotic Drilling: DPR & Hilti
DPR utilized the Hilti Concrete Drilling Robot to test how it performs alongside manual laborers in drilling holes through concrete slabs. They found that the Hilti could drill 500 holes per day while the Laborers were only able to drill 300 per day, increasing the initial productivity significantly. However, the productivity the Hilti makes in the field, it loses in the preparation of BIM documents that will need to have a higher Level of Detail, additional modeling with precise coordination, and test placements to align the BIM. If the precision was inaccurate, contractors would have to go back and drill the holes again after the slab was finished, reducing productivity by 5%.
Automated Safety: Obayashi & Stocklin
Obayashi teamed up with Stocklin to create an AGV (Automatic Guided Vehicle) to study the level of productivity, safety, and cost savings that can be achieved through robotics. The case study cites that the Ministry of Health, Labour and Welfare in Japan estimates that 15% of all construction-related injuries are caused by manually handling and moving construction materials.
The AGV was able to do the work of 5 team members, with only one operator and a support crew of 2 people, and can handle the transit of materials from over 20 contractors. In terms of safety, the MLS uses Lidar scanning to detect its surroundings and slow down or stop automatically when obstacles are detected. Along with the productivity and safety measures, the AGV is also capable of managing 68% of construction material orders.
Scaffolding Innovation: Bechtel & Kewazo
Kewazo is the developer of “Liftbot”, a semi-automatic, remote-controlled, camera assisted robot, that aids in the development of scaffolding during construction. In 2022 when the initial study was completed Kewazo planned on pairing Liftbot with digital programming called Onsite that would track and manage the scaffolding work. As of January 2023, Kawazo was able to raise $10 million to move forward in that advancement!
Bechtel tested Liftbot’s abilities on a 20-story, 40-Meter-tall project. The testing found that Liftbot was able to reduce manual labor, reduce cost, and remove limitations altogether on scaffolding-level heights, all while simultaneously tracking progress and generating online reports. Betchel calculated that a scaffolding project with Liftbot would be a little over $10,000 a month, while the typical manual process would consist of 11 team members at $55 per hour per month. Averaging out to just above $140,000 per month.
Aerial Scanning: Megacentro & Exyn
Exyn Technologies develops autonomous aerial robots designed for environments without GPS, like mines, using drones equipped with Lidar, Laser Scanning/Point Cloud Technology, and thermal cameras to map and survey hazardous areas. These drones navigate autonomously, avoiding obstacles while capturing 3D scans, and the collected data is analyzed using AI tools.
Megacentro tested the Exyn Technology at a 100,000 m² warehouse in Lurin, Peru, using drones to increase inspection frequency from once a year to twice a month. This enabled early detection of minor issues, allowing for preventive maintenance and reducing the likelihood of more significant erosion over time.
Autonomous Hauling: Produktiva & SafeAI
SafeAI has developed autonomous driving technology for construction and mining vehicles by integrating AI with advanced sensors, a drive-by-wire system, and autonomy software. This system allows light vehicles, and heavy machinery to operate autonomously, following a preset path and analyzing real-time conditions like obstacles and terrain.
Produktiva performed this study on a $6M, 23-story residential project in Lima, Peru, SafeAI’s autonomous skid steer was used to haul 700 m³ of material over 172 meters. Though the skid steer operated at a lower speed (11 km/h) for safety, future iterations aim to match typically manual operator speeds. Currently, one person supervises each machine, but the goal is to control multiple machines simultaneously.
Spot Scanning: NCC & Boston Dynamics
Boston Dynamics’, developed a robot named Spot. It has 4 legs, can be used indoors and outdoors, can navigate complex terrains, open doors with a robotic arm, and climb stairs. It is controlled by a tablet connected to Wi-Fi. In construction, Spot is used for tasks like Point Cloud Scanning, incorporating cameras from companies like Faro and Lieca. It is also used in comparing as-built conditions with BIM, monitoring safety, and tracking invoicing. Its ability to autonomously repeat programming makes it perfect for constant scans during project progression.
In a case study on the Kineum project, NCC and Platzer collaborated to retrofit two existing floors (8,000 m²) to add a 27-story hotel and offices. Two workers manually scanned these furniture-filled floors over five days, with frequent equipment shifting due to irregular room sizing. While this study focused on a one-time scan, Spot’s advantage lies in repetitive, multi-sensor scans, addressing industry labor shortages and the need for efficient scanning in the future!
Drywall Automation: Swinerton & Canvas
The Canvas robot was designed to assist with interior drywall finishing tasks such as mudding and sanding. It has a mobile platform with a robotic arm that uses two tools: a sprayer for applying drywall mud and a sander with a vacuum for smoothing surfaces. The Canvas Robot is also equipped with LiDAR sensors for mapping and calibration, the robot ensures a quality finish through force sensing and tool compliance. While mostly autonomous, it requires operator supervision for about 30% of the time, controlled through a tablet.
DPR and Swinerton, who specialize in technical and commercial buildings collaborated on this Case Study. For DPR’s pharmaceutical project, it finished 5,935 m² of drywall across 11 zones, while Swinerton had used Canvas in several smaller projects. Typically, a crew of five to seven drywall workers is needed alongside one or two robots, similar in size to traditional manual crews.
Exoskeleton Efficiency: HdLab & SuitX
ShoulderX, designed by SuitX, is an exoskeleton designed to help skilled laborers reduce fatigue while performing overhead and lifting tasks. It alleviates gravity-induced strain on the shoulders, making tasks performed from chest to ceiling easier by balancing the weight of the wearer’s arms and tools. The exoskeleton can be quickly adjusted for varying levels of support and allows for natural movement, even in confined spaces.
In Engelhoven et al., another case study done in 2018, it was found that a worker’s strength can increase by 80% through the incorporation of ShoulderX robotics. HdLab studied the overhead drilling of hanger installations, and over 1,000 holes were drilled manually. However, the SuitX takes about five minutes to put on and costs $5,000, with an additional $600 for one-time training. Labor costs remained at $43.75 per hour in both scenarios.
Drone Surveying: MT Højgaard & CivRobotics
CivRobotics developed the CivDrone for the purpose of automating survey point markers using drones alongside their & CivDot technology capable of painting the survey point layouts. The productivity and initial pricing of CivRobotics depended on factors like point distance, accuracy, terrain complexity, and battery life of the robots. MT Højgaard tested the CivDot on a 1-acre site for the Aquatics Cultural Center in Copenhagen. They typical cost for the purchase of one of these robots is between $40,000 to $60,000.
However, because MT Højgaard was unsure of the future needs of the projects, they instead chose to rent the robot for a combined total of $4,800 per month, at a lower accuracy level performance and was able to meet the needs of the project. Without robotics, this task would normally require two or more workers to manually collect the point coordinates, clear the construction site, determine the entire workspace, and place the stakes manually. With the CivDot, MT Højgaard was able to complete the task of placing 267 markers across the site, reducing the overall manual labor required, increasing accuracy, and increasing the speed of work.
Rebar Tying: Implenia & TyBot
The TyBot is a type of advanced construction robot that can automate the tying of rebars. The TyBot improves safety, and strain put onto laborers when manually performing this task. This robot can also work through temperamental weather conditions, like rain or wind. The TyBot is mounted by a rail system overhead, uses wheels to move around the rail system, and is equipped with cameras to map out the project.
Training for the robot only takes 6 days and the TyBot can only use a specific size of rebars and requires the use of a proprietary software to work properly. Implenia tested TyBot to install 18,000 m3 of reinforced slab and the Traylor Brothers tested this robot on a 1-10 twin span bridge. Both tasks would usually require extensive, strenuous labor of a group of 6-8 workers, and the scope of work usually takes up to 6 weeks to complete. The Tybot was able to complete its work within two 8 hours sessions and one team member was present to monitor progress. Similarly to previous case studies above, Although the TyBot could provide various benefits, both contractor teams felt that the technology has not yet advanced enough to commit to purchasing, so they rented the TyBot for $3,600 per week.
Final Thoughts
In conclusion, the case studies highlight the significant potential of robotics in construction, particularly in improving safety and reducing manual labor, with a 72% overall increase across all 10 robots studied. Notably, 8 out of 10 robots achieved a remarkable 55% increase in accuracy, though an average of 10% of tasks still required reworking and corrections. The financial impact varied: while six robots offered cost savings between 30-60%, four actually increased project costs by a similar margin. However, 8 of the projects were completed ahead of schedule, demonstrating the efficiency gains, despite one project taking longer than expected.
While these advancements hold promise, they also raise concerns among construction workers and architects about robotics’ role in their field. These concerns are valid, as robotics—though helpful—are not without imperfections. They currently perform on par with or marginally better than traditional methods, indicating that while the technology is advancing, it is not yet a flawless replacement for human expertise.
Ultimately, as robotics technology continues to mature, the future of construction looks to be one in which human ingenuity and robotic efficiency work together to build safer, faster, and more cost-effective structures.
