  In the dynamic construction industry, traditional robotic integration has
primarily focused on automating specific tasks, often overlooking the
complexity and variability of human aspects in construction workflows. This
paper introduces a human-centered approach with a "work companion rover"
designed to assist construction workers within their existing practices, aiming
to enhance safety and workflow fluency while respecting construction labor's
skilled nature. We conduct an in-depth study on deploying a robotic system in
carpentry formwork, showcasing a prototype that emphasizes mobility, safety,
and comfortable worker-robot collaboration in dynamic environments through a
contextual Reinforcement Learning (RL)-driven modular framework. Our research
advances robotic applications in construction, advocating for collaborative
models where adaptive robots support rather than replace humans, underscoring
the potential for an interactive and collaborative human-robot workforce.
