Human leading or following preferences: Effects on human perception of the robot and the human–robot collaboration

Abstract

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 preferences 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. • Implementing the task planning framework, adaptable to the human agent’s preference and performance, in a designed autonomous pick-and-place scenario. • Implementing dynamic task and action updates based on task states, agents’ actions, and human errors. • Investigating how the cobot’s adaptive planning influences participants’ perception of the robot and collaboration. • Exploring the influence of participants’ preferences, collaboration attitude, leadership style, and initial trust on their task planning and collaboration.