论文标题
Atlas Fusion-自主代理传感器数据融合的现代框架
Atlas Fusion -- Modern Framework for Autonomous Agent Sensor Data Fusion
论文作者
论文摘要
在本文中，我们介绍了用于自动驾驶汽车和其他自动驾驶机器人的软件传感器融合框架。我们将我们的框架设计为一个通用且可扩展的平台，可通过将各种传感器融合到数据模型中，以建立代理周围环境的强大3D模型，我们可以用作决策和计划算法的地下室。我们的软件目前涵盖了RGB和热摄像机，3D激光雷达，3D IMU和GNSS定位的数据融合。该框架涵盖了数据加载，过滤，预处理，环境模型构建，可视化和数据存储的完整管道。该体系结构允许社区修改现有设置或通过新想法扩展我们的解决方案。整个软件与ROS（机器人操作系统）完全兼容，该软件允许该框架与其他基于ROS的软件合作。根据麻省理工学院许可证，源代码可作为开源。请参阅https://github.com/robotics-but/atlas-fusion。
In this paper, we present our software sensor fusion framework for self-driving cars and other autonomous robots. We have designed our framework as a universal and scalable platform for building up a robust 3D model of the agent's surrounding environment by fusing a wide range of various sensors into the data model that we can use as a basement for the decision making and planning algorithms. Our software currently covers the data fusion of the RGB and thermal cameras, 3D LiDARs, 3D IMU, and a GNSS positioning. The framework covers a complete pipeline from data loading, filtering, preprocessing, environment model construction, visualization, and data storage. The architecture allows the community to modify the existing setup or to extend our solution with new ideas. The entire software is fully compatible with ROS (Robotic Operation System), which allows the framework to cooperate with other ROS-based software. The source codes are fully available as an open-source under the MIT license. See https://github.com/Robotics-BUT/Atlas-Fusion.
