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

Abstract

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.

Object Localization by Construction of an Asymmetric Isobody of the Magnetic Gradient Tensor Contraction Using Two Identical Permanent Magnets

“…These are usually combined with sensor fusion and simultaneous localization and mapping algorithms (SLAM). An overview of this concept can be found in [8]. However, these systems, which are within an affordable range, achieve an accuracy of about 10 cm, as shown by the example of UWB [9].…”