Adaptive Human-Robot Collaboration for Masonry Construction Under Material and Assembly Uncertainty

[2605.20264] Adaptive Human-Robot Collaboration for Masonry Construction Under Material and Assembly Uncertainty

[Submitted on 18 May 2026]

Title:Adaptive Human-Robot Collaboration for Masonry Construction Under Material and Assembly Uncertainty

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Abstract:Human-robot collaboration in construction is often challenged by limited robot-to-human communication and the need to adapt to tolerance accumulation arising from material and assembly uncertainties. We present an adaptive human-robot collaborative workflow for masonry construction that addresses communication limitations and tolerance accumulation, demonstrated through a brickwork case study in which a robot places bricks while a human applies adhesive. This workflow is enabled by two complementary mechanisms: 1) an end-effector-mounted projector that provides spatially registered, just-in-time projection guidance for manual adhesive application, and 2) laser scanning for feedback-driven grasping and placement pose correction. Together, these mechanisms enable adjustment of human and robotic actions in response to material variability and accumulated assembly tolerances. Full-scale experiments across conventional running-bond and nonstandard configurations demonstrate that projection guidance improves adhesive application consistency and reduces application time, while laser-based correction maintains level courses and avoids collision-prone failures associated with open-loop execution. These results indicate that integrating spatial projection with feedback-driven adaptation, enabled by material and as-built sensing, can mitigate tolerance accumulation and improve precision and robustness in human-robot collaborative construction.

Comments: Accepted for publication in Proceedings of the 43rd International Symposium on Automation and Robotics in Construction (ISARC 2026)

Subjects:

Robotics (cs.RO); Human-Computer Interaction (cs.HC)

Cite as: arXiv:2605.20264 [cs.RO]

(or arXiv:2605.20264v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2605.20264

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Arash Adel [view email] [v1] Mon, 18 May 2026 18:42:31 UTC (30,007 KB)

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