This paper presents the development of a co-designed timber assembly system with a mobile robotic platform for collective robotic construction (CRC) across three successive demonstrations. Iterative advances in the relationship between material, mechanical robot design, architectural design, and robotic control enable the system to advance from showcasing robotic capabilities, to realizing the planar assembly of timber struts, and finally to achieving the spatial construction of truss-like structures. The first two demonstrations established a foundation for scalable coordination between multiple small mobile robotic actuators and standardized, linear timber building elements they manipulate for 2D assembly. The third demonstration extended this CRC system to the construction of spatial assemblies, demonstrating real-time planning adjustments and the coordination of homogeneous robotic agents. This research argues that co-design, linking the various research aspects in CRC, can be leveraged in the development of systems to progressively meet more complex fabrication goals. The outcomes highlight the potential of CRC as an alternative approach to architectural construction compared to centralized, large-scale machinery workflows.
S. Leder, Hyungyu Kim, M. Sitti et al.· Construction Robotics· 0 citations
Agent-based modeling and simulation (ABMS) has been widely employed to study emergent processes in collective robotic construction (CRC), where global architectural structures arise from local agent interactions. While these approaches reveal how complex assemblies can emerge without centralized control, they remain limited when an architectural goal is known but the behaviors required to achieve it are not. Most CRC workflows still depend on handcrafted heuristics. This paper presents a hybrid CRC workflow that integrates large language models (LLM) into the ABMS behavior design process. The system enables human–AI co-creation of robot behaviors, allowing an LLM agent to generate and negotiate behavioral strategies toward user-defined construction goals under partial observability. The approach is evaluated in simulation, comparing an LLM–heuristic hybrid against a heuristic-only baseline behavior. For well-documented swarm patterns, the LLM matches heuristic performance; for geometrically novel tasks, handcrafted heuristics retain an advantage. By embedding language-based reasoning within ABMS, this work expands participation in CRC behavior design and demonstrates a pathway for translating high-level design intent into adaptive, goal-oriented multiagent construction processes.
Samuel Slezák, Lasath Siriwardena, S. Leder et al.· Construction Robotics· 0 citations
