Node to process Point Cloud Data of the Radar to obtain the Body Frame Velocity
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Updated
Jun 24, 2024 - C++
Node to process Point Cloud Data of the Radar to obtain the Body Frame Velocity
Code release for "The Importance of Coordinate Frames in Dynamic SLAM", ICRA 2024
LIO_SAM for 6-axis IMU and GNSS.
IMU-based human skeletal pose estimation in C++11
Factored inference for discrete-continuous smoothing and mapping.
The tight integration of FAST-LIO with Radius-Search-based loop closure module.
Robust LiDAR SLAM with a versatile plug-and-play loop closing and pose-graph optimization.
GTSAM <-> mrpt-serialization bridge
LIO-SAM-6AXIS with intensity image loop optimization
My personal solution for "AirLab Summer School Session 2.2"
SRSLAM: SCUT RobotLab Simultaneous Localization And Mapping
A real-time LiDAR SLAM package that integrates FLOAM and ScanContext.
Car-like vehicle path planning using graph optimization - GTSAM lib
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