Feedback-driven adaptive multi-robot timber construction

Arash Adel, Daniel Ruan, Wesley McGee, Salma Mozaffari

Research output: Contribution to journalArticlepeer-review

Abstract

Automation and robotics are anticipated to play a crucial role in addressing challenges confronting the construction industry, such as low productivity, workforce shortages, and physically demanding labor. However, a critical challenge in construction robotics has been the development of robust adaptive control to deal with uncertainties inherent in construction, such as material imperfections, multi-robot calibration, and fabrication inaccuracies. To address this challenge, we present a feedback-driven framework consisting of two complementary adaptive fabrication methods, pose-based and topology-based, incorporating perception, reasoning, and acting to handle uncertainties in multi-robot timber construction. We evaluate our framework through building-scale experiments, quantifying their deviations from their as-planned digital models. Our results indicate that our pose-based method significantly decreased deviations compared to a benchmark when applied to nail-laminated timber panels, and our topology-based method enabled robust multi-robot construction of a timber frame wall. Altogether, this research contributes to flexible, accurate, and robust construction employing multi-robot systems.

Original languageEnglish (US)
Article number105444
JournalAutomation in Construction
Volume164
DOIs
StatePublished - Aug 2024

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction

Keywords

  • Adaptive fabrication
  • Construction automation
  • Cooperative robotics
  • Iterative learning control
  • Multi-robot construction
  • Robotic assembly
  • Timber construction

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