多机器人去中心化协作SLAM在类地环境中的应用：数据集、挑战与经验教训
Multi-Robot Decentralized Collaborative SLAM in Planetary Analogue Environments: Dataset, Challenges, and Lessons Learned
AI总结：
本文提出了一种在类地环境中实现多机器人去中心化协作SLAM的方法，并介绍了用于支持通信受限多机器人操作的新数据集。
摘要：
去中心化协作的同时定位与建图（C-SLAM）是实现未知环境中多机器人任务的关键，无需依赖预先存在的定位和通信基础设施。这项技术预计将在月球、火星及其他行星的探索中发挥重要作用。本文分享了涉及三个机器人在火星类比地形上操作并通过临时网络通信的C-SLAM实验所获得的见解和经验。我们研究了有限且间歇性通信对C-SLAM性能的影响，以及类行星环境带来的独特定位挑战。此外，我们介绍了一个新的数据集，其中包括实验期间实时的点对点机器人之间吞吐量和延迟测量。该数据集旨在支持未来研究通信受限的去中心化多机器人操作。
英文摘要：
Decentralized collaborative simultaneous localization and mapping (C-SLAM) is essential to enable multirobot missions in unknown environments without relying on preexisting localization and communication infrastructure. This technology is anticipated to play a key role in the exploration of the Moon, Mars, and other planets. In this article, we share insights and lessons learned from C-SLAM experiments involving three robots operating on a Mars analogue terrain and communicating over an ad hoc network. We examine the impact of limited and intermittent communication on C-SLAM performance, as well as the unique localization challenges posed by planetary-like environments. Additionally, we introduce a novel dataset collected during our experiments, which includes real-time peer-to-peer inter-robot throughput and latency measurements. This dataset aims to support future research on communication-constrained, decentralized multirobot operations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
