论文标题
增强的激光惯性大满贯系统，用于机器人的本地化和映射
An Enhanced LiDAR-Inertial SLAM System for Robotics Localization and Mapping
论文作者
论文摘要
基于激光剂和基于惯性传感器的定位和映射对于无人机相关的应用具有重要意义。在这项工作中，我们为无人接地车开发了改进的激光惯性定位和映射系统，这适用于多功能搜索和救援应用。与现有的基于LiDAR的定位和诸如壤土之类的映射系统相比，我们有两个主要贡献：第一个是改善基于粒子群体滤波器过滤器的LIDAR SLAM的鲁棒性，而第二个是开发的循环闭合方法，用于全局优化，以提高整个系统的本地化精度。我们通过实验证明，激光雷达大满贯系统的准确性和鲁棒性都得到了提高。最后，我们在香港科学园以及其他室内或室外实际复杂的测试情况进行了系统的实验测试，这证明了我们方法的有效性和效率。证明我们的系统具有很高的精度，鲁棒性和效率。我们的系统对于在未知环境中无人接地车的本地化和映射至关重要。
The LiDAR and inertial sensors based localization and mapping are of great significance for Unmanned Ground Vehicle related applications. In this work, we have developed an improved LiDAR-inertial localization and mapping system for unmanned ground vehicles, which is appropriate for versatile search and rescue applications. Compared with existing LiDAR-based localization and mapping systems such as LOAM, we have two major contributions: the first is the improvement of the robustness of particle swarm filter-based LiDAR SLAM, while the second is the loop closure methods developed for global optimization to improve the localization accuracy of the whole system. We demonstrate by experiments that the accuracy and robustness of the LiDAR SLAM system are both improved. Finally, we have done systematic experimental tests at the Hong Kong science park as well as other indoor or outdoor real complicated testing circumstances, which demonstrates the effectiveness and efficiency of our approach. It is demonstrated that our system has high accuracy, robustness, as well as efficiency. Our system is of great importance to the localization and mapping of the unmanned ground vehicle in an unknown environment.
