与制图师一起飞行:适应制图师3D图形SLAM堆栈用于无人机导航

2021 Aerial Robotic Systems Physically Interacting with the Environment (AIRPHARO) Pub Date : 2021-06-04 DOI:10.1109/AIRPHARO52252.2021.9571065

Juraj Orsuli'c, Robert Milijas, Ana Batinovic, Lovro Markovic, Antun Ivanovic, S. Bogdan

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引用次数: 3

摘要

本文描述了在无人机反馈控制回路中，将制图器SLAM堆栈作为姿态传感器的应用，并对SLAM堆栈进行了一些特定的应用变化，如优化姿态的平滑。通过姿态图优化，将基于3D LiDAR/ imu的本体感觉与GPS位置测量相融合，进行姿态估计。此外，从Cartographer SLAM堆栈中的LiDAR数据(子地图)构建的部分环境地图被编组到OctoMap中，这是一种基于octree的体素地图实现。OctoMap进一步用于导航任务，如路径规划和避障。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Flying with Cartographer: Adapting the Cartographer 3D Graph SLAM Stack for UAV Navigation

This paper describes an application of the Cartographer graph SLAM stack as a pose sensor in a UAV feedback control loop, with certain application-specific changes in the SLAM stack such as smoothing of the optimized pose. Pose estimation is performed by fusing 3D LiDAR/IMU-based proprioception with GPS position measurements by means of pose graph optimisation. Moreover, partial environment maps built from the LiDAR data (submaps) within the Cartographer SLAM stack are marshalled into OctoMap, an Octree-based voxel map implementation. The OctoMap is further used for navigation tasks such as path planning and obstacle avoidance.

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2021 Aerial Robotic Systems Physically Interacting with the Environment (AIRPHARO)

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