This work presents a 3D multi-robot exploration framework for a team of UGVs moving on uneven terrains. The framework was designed by casting the two-level coordination strategy presented in [1] into the context of multi-robot exploration. The resulting distributed exploration technique minimizes and explicitly manages the occurrence of conflicts and interferences in the robot team. Each robot selects where to scan next by using a receding horizon next-best-view approach [2]. A sampling-based tree is directly expanded on segmented traversable regions of the terrain 3D map to generate the candidate next viewpoints. During the exploration, users can on-demand assign locations with higher priorities to steer the robot exploration toward areas of interest. The proposed framework can be also used to perform coverage tasks in the case a map of the environment is a priori provided as input. An open-source implementation is available online.

翻译：本文提出了一种面向非平坦地形上多台无人地面车辆（UGV）的三维多机器人探索框架。该框架通过将文献[1]提出的双层协调策略融入多机器人探索场景设计而成。所得到的分布式探索技术能够最小化并显式管理机器人团队中冲突与干扰的发生。每台机器人采用递推视界下一最佳视角方法[2]选择下一个扫描位置，通过在地形三维地图中分割的可通行区域上直接扩展基于采样的树结构，生成候选下一视点。在探索过程中，用户可按需分配更高优先级的区域，引导机器人向感兴趣区域推进。若环境地图预先作为输入提供，本框架还可用于执行覆盖任务。相关开源实现已在线公开。