  Achieving effective and seamless human-robot collaboration requires two key
outcomes: enhanced team performance and fostering a positive human perception
of both the robot and the collaboration. This paper investigates the capability
of the proposed task planning framework to realize these objectives by
integrating human leading/following preference and performance into its task
allocation and scheduling processes. We designed a collaborative scenario
wherein the robot autonomously collaborates with participants. The outcomes of
the user study indicate that the proactive task planning framework successfully
attains the aforementioned goals. We also explore the impact of participants'
leadership and followership styles on their collaboration. The results reveal
intriguing relationships between these factors, which warrant further
investigation in future studies.
