LIO_SAM for 6-axis IMU and GNSS.
Robust LiDAR SLAM with a versatile plug-and-play loop closing and pose-graph optimization.
The tight integration of FAST-LIO with Radius-Search-based loop closure module.
[TMECH'2024] Official codes of ”PALoc: Advancing SLAM Benchmarking with Prior-Assisted 6-DoF Trajectory Generation and Uncertainty Estimation“
A collection of GTSAM factors and optimizers for point cloud SLAM
For an education purpose, from-scratch, single-file, python-only pose-graph optimization implementation
[ICRA@40] MS-Mapping: An Uncertainty-Aware Large-Scale Multi-Session LiDAR Mapping System
Factored inference for discrete-continuous smoothing and mapping.
Offical code release for DynoSAM: Dynamic Object Smoothing And Mapping [Submitted TRO Visual SLAM SI]. A visual SLAM framework and pipeline for Dynamic environements, estimating for the motion/pose of...
Visual Inertial Odometry (VIO) / Simultaneous Localization & Mapping (SLAM) using iSAM2 framework from the GTSAM library.
Lightweighted graph optimization (Factor graph) library.
learning and feeling SLAM together with hands-on-experiments
The full_linear_wheel_odometry_factor provides motion constraints and online calibration for skid-steering robots. This constraint can be incorporated into your SLAM framework. Here is an example vide...
LIO-SAM-6AXIS with intensity image loop optimization
Software Release for "Incremental Covariance Estimation for Robust Localization"
Code release for "Evaluation of Precise Point Positioning Convergence with an Incremental Graph Optimizer".
IMU-based human skeletal pose estimation in C++11