Modular vehicles present a novel area of academic and industrial interest in the field of multi-agent systems. Modularity allows vehicles to connect and disconnect with each other mid-transit which provides a balance between efficiency and flexibility when solving complex and large scale tasks in urban or aerial transportation. This paper details a generalized scheme to route multiple modular agents on a graph to a predetermined set of target nodes. The objective is to visit all target nodes while incurring minimum resource expenditure. Agents that are joined together will incur the equivalent cost of a single agent, which is motivated by the logistical benefits of traffic reduction and increased fuel efficiency. To solve this problem, we introduce a novel algorithm that seeks to balance the optimality of the path that every single module takes and the cost benefit of joining modules. Our approach models the agents and targets as point charges, where the modules take the path of highest attractive force from its target node and neighboring agents. We validate our approach by simulating multiple modular agents along real-world transportation routes in the road network of Champaign-Urbana, Illinois, USA. The proposed method easily exceeds the available benchmarks and illustrates the benefits of modularity in multi-target planning problems.

翻译：模块化车辆是多智能体系统领域中一个新兴的学术与工业研究方向。模块化特性使得车辆能够在运输途中相互连接或分离，从而在城市或空中交通场景中解决复杂大规模任务时，在效率与灵活性之间取得平衡。本文详述了一种在图上将多个模块化智能体路由至预定目标节点集的通用方案。其目标是在访问所有目标节点的同时实现资源消耗最小化。连接状态的智能体仅需承担单个智能体的等效成本，这一设计源于减少交通流量与提升燃油效率的物流效益考量。为解决该问题，我们提出一种新颖算法，旨在平衡每个独立模块的路径最优性与模块连接带来的成本效益。我们的方法将智能体与目标建模为点电荷，模块将沿着来自其目标节点及相邻智能体的最大吸引力方向行进。我们通过在美国伊利诺伊州尚佩恩-厄巴纳市真实道路网络上模拟多个模块化智能体的运输路线来验证所提方法。实验表明，该方案显著超越了现有基准，并充分展示了模块化在多目标规划问题中的优势。