论文标题
使用实时重新整合和主动循环封闭的探索全球一致性
Exploration with Global Consistency Using Real-Time Re-integration and Active Loop Closure
论文作者
论文摘要
尽管机器人探索最近进展，但大多数方法都认为可以使用无漂移的定位，这在现实中是有问题的，并且会导致重建的地图的严重失真。在这项工作中，我们提出了一个系统的探索映射和计划框架，该框架涉及漂移的本地化，从而允许有效且在全球一致的重建。提出了一种基于实时重新整合的映射方法以及框架修剪机制，该方法在检测到环闭合时校正漂移定位时有效地纠正了MAP失真。此外，提出了一种考虑历史观点的探索计划方法，以实现主动循环结束，这促进了更高的机会来纠正本地化错误并进一步提高映射质量。我们在模拟和现实世界实验中全面评估了映射和计划方法以及整个系统，显示了它们在实践中的有效性。将实施该方法的实施，以使机器人社区受益。
Despite recent progress of robotic exploration, most methods assume that drift-free localization is available, which is problematic in reality and causes severe distortion of the reconstructed map. In this work, we present a systematic exploration mapping and planning framework that deals with drifted localization, allowing efficient and globally consistent reconstruction. A real-time re-integration-based mapping approach along with a frame pruning mechanism is proposed, which rectifies map distortion effectively when drifted localization is corrected upon detecting loop-closure. Besides, an exploration planning method considering historical viewpoints is presented to enable active loop closing, which promotes a higher opportunity to correct localization errors and further improves the mapping quality. We evaluate both the mapping and planning methods as well as the entire system comprehensively in simulation and real-world experiments, showing their effectiveness in practice. The implementation of the proposed method will be made open-source for the benefit of the robotics community.
