论文标题
全球一致并紧密耦合3D激光镜惯性映射
Globally Consistent and Tightly Coupled 3D LiDAR Inertial Mapping
论文作者
论文摘要
本文基于全球匹配成本最小化和LIDAR-IMU紧密耦合提供了实时的3D映射框架。所提出的框架包括一个预处理模块和三个估计模块：探测仪估计，局部映射和全局映射，它们都是基于GPU加速的Voxelated voxelized GICP匹配成本因子和IMU预共聚因子的紧密耦合。 ODMOTIENTRY估计模块采用基于密钥帧的固定LAG平滑方法，以实现有限的计算成本，以进行有效和低矮的轨迹估计。全局映射模块构建了一个因子图，该因素图在IMU约束的支持下将整个地图上的全局注册误差最小化，从而确保在无功能环境中进行了强大的优化。在新的大学数据集和Kaist Urban数据集上的评估结果表明，该框架可以在充满挑战的环境中准确，稳健的本地化和映射。
This paper presents a real-time 3D mapping framework based on global matching cost minimization and LiDAR-IMU tight coupling. The proposed framework comprises a preprocessing module and three estimation modules: odometry estimation, local mapping, and global mapping, which are all based on the tight coupling of the GPU-accelerated voxelized GICP matching cost factor and the IMU preintegration factor. The odometry estimation module employs a keyframe-based fixed-lag smoothing approach for efficient and low-drift trajectory estimation, with a bounded computation cost. The global mapping module constructs a factor graph that minimizes the global registration error over the entire map with the support of IMU constraints, ensuring robust optimization in feature-less environments. The evaluation results on the Newer College dataset and KAIST urban dataset show that the proposed framework enables accurate and robust localization and mapping in challenging environments.
