This paper presents a Mixed-Initiative (MI) framework for addressing the problem of control authority transfer between a remote human operator and an AI agent when cooperatively controlling a mobile robot. Our Hierarchical Expert-guided Mixed-Initiative Control Switcher (HierEMICS) leverages information on the human operator's state and intent. The control switching policies are based on a criticality hierarchy. An experimental evaluation was conducted in a high-fidelity simulated disaster response and remote inspection scenario, comparing HierEMICS with a state-of-the-art Expert-guided Mixed-Initiative Control Switcher (EMICS) in the context of mobile robot navigation. Results suggest that HierEMICS reduces conflicts for control between the human and the AI agent, which is a fundamental challenge in both the MI control paradigm and also in the related shared control paradigm. Additionally, we provide statistically significant evidence of improved, navigational safety (i.e., fewer collisions), LOA switching efficiency, and conflict for control reduction.
翻译:本文介绍了在合作控制移动机器人时,解决远程人类操作员和AI代理商之间控制权转移问题的混合倡议框架。我们的高级专家制混合倡议控制开关(HierEMICS)利用关于人类操作员状态和意图的信息。控制转换政策基于临界等级等级。在高度不端模拟灾害反应和远程检查假设中进行了实验性评价,将HierEMICS与最先进的专家制混合倡议控制开关(EMICS)在移动机器人导航中进行比较。结果显示HierEMICS减少了人类与AI代理商之间的控制冲突,这是MI控制模式和相关的共同控制模式中的一个基本挑战。此外,我们提供了关于改进航行安全(即减少碰撞)、LOA转换效率和减少控制冲突的重要统计证据。