Autonomous Aerial Robotic Exploration of Subterranean Environments relying on Morphology–aware Path Planning
Autonomous Aerial Robotic Exploration of Subterranean Environments relying on Morphology–aware Path Planning
复制标题
依靠形态感知路径规划的自主空中机器人探索地下环境
DOI：
--
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
K. Alexis
中科院分区：
文献类型：
--
作者：
C. Papachristos;Shehryar Khattak;Frank Mascarich;Tung Dang;K. Alexis
在这项工作中，自主导航，勘探和测绘在地下矿山使用空中机器人的挑战。尽管进入地下矿井至关重要，但传感器退化（黑暗、灰尘、烟雾）的相关挑战以及由于非常长的巷道中特别狭窄的几何形状而导致的广泛严格的导航条件使得典型的导航和规划方法不足。为了实现全面的解决方案，我们提出并广泛地现场测试了各种机器人实现，在地下矿山环境中实施不同的传感器融合和路径规划策略。我们得出结论，并提出了一个优化的多模态传感器融合方法，结合当地环境形态感知的探索路径规划策略，在他们的组合提供上级的结果，在导航的足智多谋和弹性，探索效率和映射精度，尽管遇到了大量的挑战性条件。
In this work the challenge of autonomous navigation, exploration and mapping in underground mines using aerial robots is considered. Despite the paramount importance of underground mine accessing, the relevant challenges of sensor degradation (darkness, dust, smoke) and broadly stringent navigation conditions due to particularly narrow geometries across very long drifts render typical navigation and planning methods insufficient. Towards a comprehensive solution, we present and extensively field test a variety of robot realizations implementing different sensor fusion and path planning strategies inside underground mine settings. We conclude and propose an optimized multi–modal sensor fusion approach combined with a local environment morphology–aware exploration path planning strategy that in their combination provide superior results in terms of navigation resourcefulness and resilience, exploration efficiency and mapping accuracy despite the large set of challenging conditions encountered.