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.
Visual Inertial Odometry (VIO) / Simultaneous Localization & Mapping (SLAM) using iSAM2 framework from the GTSAM library.
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...
Lightweighted graph optimization (Factor graph) library.
learning and feeling SLAM together with hands-on-experiments
LIO-SAM-6AXIS with intensity image loop optimization
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...
Software Release for "Incremental Covariance Estimation for Robust Localization"
Code release for "Evaluation of Precise Point Positioning Convergence with an Incremental Graph Optimizer".
Lidar localization system with prior map constraint and lio constraint based on GTSAM