We consider the NP-hard problem of multirobot informative path planning in the presence of communication constraints, where the objective is to collect higher amounts of information of an ambient phenomenon. We propose a novel approach that uses continuous region partitioning into Voronoi components to efficiently divide an initially unknown environment among the robots based on newly discovered obstacles enabling improved load balancing between robots. Simulation results show that our proposed approach is successful in reducing the initial imbalance of the robots’ allocated free regions while ensuring close-to-reality spatial modeling within a reasonable amount of time.

中文翻译：

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未知环境下通过连续区域划分的多机器人信息路径规划

我们考虑了在存在通信约束的情况下多机器人信息路径规划的 NP 难题，其目标是收集更多环境现象的信息。我们提出了一种新方法，该方法使用连续区域划分为 Voronoi 组件，以基于新发现的障碍物在机器人之间有效划分最初未知的环境，从而改善机器人之间的负载平衡。仿真结果表明，我们提出的方法成功地减少了机器人分配的自由区域的初始不平衡，同时确保在合理的时间内进行接近现实的空间建模。