2024/12/30 by Jonathan Külz, Michael Terzer, Külz, Jonathan +7 · 2 citations
Engineering · #Artificial Intelligence (cs.AI) #BIM and Construction Integration #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Innovations in Concrete and Construction Materials #Modular Robots and Swarm Intelligence #Robotics (cs.RO)
paper · pdf · doi:10.48550/arxiv.2412.20867
openalex publication_date 2024/12/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In situ robotic automation in construction is challenging due to constantly changing environments, a shortage of robotic experts, and a lack of standardized frameworks bridging robotics and construction practices. This work proposes a holistic framework for construction task specification, optimization of robot morphology, and mission execution using a mobile modular reconfigurable robot. Users can specify and monitor the desired robot behavior through a graphical interface. In contrast to existing, monolithic solutions, we automatically identify a new task-tailored robot for every task by integrating \acfbim. Our framework leverages modular robot components that enable the fast adaption of robot hardware to the specific demands of the construction task. Other than previous works on modular robot optimization, we consider multiple competing objectives, which allow us to explicitly model the challenges of real-world transfer, such as calibration errors. We demonstrate our framework in simulation by optimizing robots for drilling and spray painting. Finally, experimental validation demonstrates that our approach robustly enables the autonomous execution of robotic drilling.