Exercise of robotics in many applications brings in concerns of human–robot interaction. This paper offers a mathematical model-based mission planning tool for optimizing operator workload and platform utilization in human/multi-robot (H/M-R) teams. None of the earlier methods consistently predicts fan-out (number and configuration of robots that can be operated simultaneously and effectively, a critical H/M-R design decision). In this research, a mixed integer programming (MIP) model and solution framework are proposed to provide better estimates of fan-out while explicitly considering the performance, mission characteristics, objective and task/environment complexity. The extent of each robot’s waiting time is restricted by a utilization threshold in the MIP model. The effect of environment’s complexity on the task effectiveness is considered, where robots’ performances deteriorate during switch and neglect times. Simulation results show that fan-out effect is dependent on interaction efficiency, neglect tolerance, as well as other parameters. Performance is most sensitive to environment’s complexity and least sensitive to utilization threshold. In addition, the MIP model reveals optimal control sequence of robots to prevent switching confusions and maximize team performance. Empirical evaluations show that this approach holds great promise for real-world scenarios.

中文翻译：

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混合整数编程（MIP）模型，用于评估人机交互（HRI）的导航和任务计划

在许多应用中使用机器人技术会引发人机交互的问题。本文提供了一种基于数学模型的任务计划工具，用于优化人/多机器人（H / MR）团队的操作员工作量和平台利用率。较早的方法都无法始终预测扇出（可同时有效运行的机器人的数量和配置，这是关键的H / MR设计决策）。在这项研究中，提出了一种混合整数规划（MIP）模型和解决方案框架，以提供更好的扇出估计，同时明确考虑性能，任务特性，目标和任务/环境复杂性。每个机器人的等待时间范围受MIP模型中的利用率阈值限制。考虑了环境复杂性对任务有效性的影响，在切换和忽略时间内，机器人的性能会下降。仿真结果表明，扇出效应取决于交互效率，忽略容忍度以及其他参数。性能对环境的复杂度最敏感，而对利用率阈值最不敏感。另外，MIP模型揭示了机器人的最佳控制顺序，以防止切换混乱并最大化团队绩效。实证评估表明，这种方法在现实世界中具有广阔的前景。MIP模型揭示了机器人的最佳控制顺序，以防止切换混乱并最大化团队绩效。实证评估表明，这种方法在现实世界中具有广阔的前景。MIP模型揭示了机器人的最佳控制顺序，以防止切换混乱并最大化团队绩效。实证评估表明，这种方法在现实世界中具有广阔的前景。