Quantum Computing for Construction Robots: Challenges and Opportunities
Ci‐Jyun Liang, Logan Norton-Lapsley, Zhaofeng Hu
Construction robotics play a crucial role in the architecture, engineering, and construction (AEC) industry, but they face significant computational challenges due to dynamic environments, multi-agent coordination, and largescale combinatorial optimization problems.Quantum computing (QC) offers potential advantages for large-scale search and combinatorial tasks, but its relevance to construction robotics remains unclear.This paper presents a scoping review of QC in robotics.We first collect literature using keyword search from Scopus and Web of Science databases, and then screen through data and include related literature following PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews).We analyze the 96 included studies using bibliometric and thematic analyses to identify research trends and challenges for construction robotics.Results show growing interest in QC robotics since 2020, with dominant applications in path planning, kinematics and control, multi-robot coordination, and decision-making.We identify key barriers to applying QC in construction robotics, including current hardware limitations, simulation-to-real gaps, stringent safety and explainability requirements, and suggest future research directions, including hybrid quantum-classical approaches, QC robotics benchmarks, and explainable QC.
International Symposium on Automation and Robotics in Construction (ISARC)•Jun 22, 2026•0 citations