论文标题
狼牙棒：多代理自动协作探索未知环境
MACE: Multi-Agent Autonomous Collaborative Exploration of Unknown Environments
论文作者
论文摘要
在本文中，我们提出了一个新的框架，用于对未知环境的多代理协作探索。所提出的方法结合了映射，安全的走廊生成和多代理计划中的最新算法。它首先需要我们要探索的卷，然后继续为多个代理提供不同的目标，以探索该卷的素脉网格。当所有体素被发现为自由或占据时，探索结束了，或者没有发现其余未发现的体素的路径。最先进的计划算法使用时间认知的安全走廊来确保机体内碰撞安全以及静态障碍物的安全性。提出的方法以最多4个代理商的最新模拟器状态进行了测试。
In this paper, we propose a new framework for multi-agent collaborative exploration of unknown environments. The proposed method combines state-of-the-art algorithms in mapping, safe corridor generation and multi-agent planning. It first takes a volume that we want to explore, then proceeds to give the multiple agents different goals in order to explore a voxel grid of that volume. The exploration ends when all voxels are discovered as free or occupied, or there is no path found for the remaining undiscovered voxels. The state-of-the-art planning algorithm uses time-aware Safe Corridors to guarantee intra-agent collision safety as well safety from static obstacles. The presented approach is tested in a state of the art simulator for up to 4 agents.
