English

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

Robotics 2026-05-21 v1 Human-Computer Interaction

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.

Keywords

Cite

@article{arxiv.2605.20264,
  title  = {Adaptive Human-Robot Collaboration for Masonry Construction Under Material and Assembly Uncertainty},
  author = {Jutang Gao and Arash Adel},
  journal= {arXiv preprint arXiv:2605.20264},
  year   = {2026}
}

Comments

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

R2 v1 2026-07-22T07:22:27.732Z