  Though construction robots have drawn attention in research and practice for
decades, human-robot collaboration (HRC) remains important to conduct complex
construction tasks. Considering its complexity and uniqueness, it is still
unclear how HRC process will impact construction productivity. To this end, an
agent-based (AB) multi-fidelity modeling approach is introduced to simulate and
evaluate how HRC influences construction productivity. A high-fidelity model is
first proposed for a scenario with one robot. Then, a low-fidelity model is
established to extract key parameters that capture the inner relationship among
scenarios. The multi-fidelity models work together to simulate complex
scenarios. Simulation and experiements show that: 1) the proposed approach is
feasible and flexible for simulation of complex HRC processes, and can cover
multiple collaboration and interaction modes; 2) the influence of the
supplement strategy is simple when there is only one robot, where lower Check
Interval (CI) and higher Supplement Limit (SL) will improve productivity. But
the influence becomes much more complicated when there are more robots due to
the internal competition among robots for the limited time of workers; 3) the
productivity per robot improves when there are more robots and workers, even if
the human-robot ratio remains the same; 4) introducing proactive interaction
between robots and workers could improve productivity significantly, up to 22%
in our experiments, which further depends on the supplement strategy and the
human-robot ratio. Overall, this research contributes an integrated approach to
simulate and evaluate HRC's impacts on productivity as well as valuable
insights on how to optimize HRC for better performance.
