Adaptive task planning is fundamental to ensuring effective and seamless human-robot collaboration. This paper introduces a robot task planning framework that takes into account both human leading/following preferences and performance, specifically focusing on task allocation and scheduling in collaborative settings. We present a proactive task allocation approach with three primary objectives: enhancing team performance, incorporating human preferences, and upholding a positive human perception of the robot and the collaborative experience. Through a user study, involving an autonomous mobile manipulator robot working alongside participants in a collaborative scenario, we confirm that the task planning framework successfully attains all three intended goals, thereby contributing to the advancement of adaptive task planning in human-robot collaboration. This paper mainly focuses on the first two objectives, and we discuss the third objective, participants' perception of the robot, tasks, and collaboration in a companion paper.

翻译：自适应任务规划是确保高效且无缝人机协作的基础。本文提出了一种机器人任务规划框架，该框架综合考虑了人类的领航/跟随偏好与表现，尤其关注协作场景中的任务分配与调度。我们提出了一种主动式任务分配方法，旨在实现三个主要目标：提升团队绩效、融入人类偏好，以及维持人类对机器人及协作体验的积极感知。通过一项用户研究（涉及一台自主移动机械臂机器人在协作场景中与参与者协同工作），我们验证了该任务规划框架成功实现了所有三个既定目标，从而为人机协作中自适应任务规划的发展做出了贡献。本文主要聚焦于前两个目标，第三个目标（参与者对机器人、任务及协作的感知）将在配套论文中详细讨论。