In this paper, we present a novel problem coined multi-robot, multi-objective, and multi-mode routing and scheduling (M^3RS). The formulation for M^3RS is introduced for time-bound multi-robot, multi-objective routing and scheduling missions where each task has multiple execution modes. Different execution modes have distinct resource consumption, associated execution time, and quality. M^3RS assigns the optimal sequence of tasks and the execution modes to each agent. The routes and associated modes depend on user preferences for different objective criteria. The need for M^3RS comes from multi-robot applications in which a trade-off between multiple criteria arises from different task execution modes. We use M^3RS for the application of multi-robot disinfection in public locations. The objectives considered for disinfection application are disinfection quality and number of tasks completed. A mixed-integer linear programming model is proposed for M^3RS. Then, a time-efficient column generation scheme is presented to tackle the issue of computation times for larger problem instances. The advantage of using multiple modes over fixed execution mode is demonstrated using experiments on synthetic data. The results suggest that M^3RS provides flexibility to the user in terms of available solutions and performs well in joint performance metrics. The application of the proposed problem is shown for a team of disinfection robots.} The videos for the experiments are available on the project website: https://sites.google.com/view/g-robot/m3rs/ .

翻译：本文提出一个新颖问题——多机器人、多目标与多模式路径规划与调度（M^3RS）。该问题针对时间受限的多机器人、多目标路径规划与调度任务，其中每个任务具有多种执行模式。不同执行模式在资源消耗、执行时间和任务质量上存在差异。M^3RS为每个智能体分配最优任务序列及执行模式，其路径和模式选择取决于用户对不同目标准则的偏好。该问题的提出源于多机器人应用中不同任务执行模式引发的多准则权衡需求。我们将M^3RS应用于公共场所的多机器人消毒任务，考虑的优化目标包括消毒质量与完成的任务数量。针对M^3RS建立混合整数线性规划模型，并提出一种时间高效的列生成方案以应对大规模实例的计算时间问题。通过合成数据实验验证了多模式相较于固定执行模式的优越性。结果表明，M^3RS在可用解空间方面为用户提供灵活性，并在联合性能指标上表现优异。最后以消毒机器人团队为例展示了所提问题的实际应用场景。实验视频详见项目网站：https://sites.google.com/view/g-robot/m3rs/。