Towards Autonomous Bricklaying Using Boston Dynamics Spot
Authors: Karl-Johan Sorensen, Nico vom Hofe, Frank H. P. Fitzek
Organizations: Department of Architecture, Massachusetts Institute of Technology, United States · Deutsche Telekom Chair of Communication Networks, TU Dresden, Germany · Centre for Tactile Internet with Human-in-the-Loop (CeTI), Dresden, Germany
Mobile legged robots offer unique advantages for on-site construction, including the ability to traverse unstructured terrain, climb stairs, and operate independently between spatially separated work zones. This paper presents a proof-of-concept system for autonomous brick stacking using a Boston Dynamics Spot quadrupedal robot equipped with a manipulator arm. The system operates between a supply area and an assembly area, using AprilTag fiducials for localization and autowalk missions for navigation. Target brick positions and orientations are specified in CAD software and exported directly for robotic execution. We evaluate placement accuracy through ten repeated assemblies of a curved four-layer wall comprising 14 wooden bricks. Results show mean translation errors below 10 mm and mean yaw errors below 1.5 degrees, while the overall RMSE across all runs is 27.72 mm (translation) and 2.06 degrees (rotation). The system was also tested outdoors with stairs between the two areas. The workflow is modular and easily extendable to different wall geometries.
Figures & tables
Figure 1: System overview
Figure 2: Spot after placing a brick on a curved wall
Figure 3: Superimposed video frames from the experiment showing Spot at pick position (1), autowalking (2), and at place position (3)
Figure 4: Superimposed overlay of all ten first-layer placements, showing variability across runs
Figure 5: Error metrics for the individual layers
Operation
Duration (s)
Pick
9.18
Walk to assembly area
15.46
Place
9.68
Walk to supply area
16.15
Total cycle
50.47
Table 1: Mean cycle times for each operation phase
Figure 6: Autonomous construction scenario in an outdoor setting including stairways
Figure 7: Brick detection model detecting a brick with 75% confidence; showing the bounding box and center point