Recent years have seen an increasing number of deployment of fleets of autonomous vehicles. As the problem scales up, in terms of autonomous vehicles number and complexity of their objectives, there is a growing need for decision-support tooling to help the operators in controlling the fleet. In this paper, we present an automated planning system developed to assist the operators in the CoHoMa II challenge, where a fleet of robots, remotely controlled by a handful of operators, must explore and progress through a potential hostile area. In this context, we use planning to provide the operators with suggestions about the actions to consider and their allocation to the robots. This paper especially focus on the modelling of the problem as a hierarchical planning problem for which we use a state-of-the-art automated solver.

翻译：近年来，自动驾驶车队部署数量日益增长。随着自主车辆数量及其目标复杂性的规模扩大，操作员对决策支持工具的需求与日俱增，以帮助他们控制车队。本文介绍了一种自动化规划系统，用于支持CoHoMa II挑战赛中的操作员——在该挑战赛中，由少数操作员远程控制的机器人车队需探索并通过潜在危险区域。在此背景下，我们利用规划技术为操作员提供关于待执行动作及其分配至机器人的建议。本文特别侧重于将该问题建模为分层规划问题，并采用最先进的自动求解器进行求解。