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dso

Direct Sparse Odometry

dynamic-occupancy-grid-map

Implementation of A Random Finite Set Approach for Dynamic Occupancy Grid Maps with Real-Time Application

dynamic_robot_localization

Point cloud registration pipeline for robot localization and 3D perception

eagleye

Precise localization based on GNSS and IMU.

elasticfusion

Real-time dense visual SLAM system

erasor

Official page of ERASOR RA-L with ICRA'21

ethzasl_msf

MSF - Modular framework for multi sensor fusion based on an Extended Kalman Filter (EKF)

event-based_vision_resources

evo

Python package for the evaluation of odometry and SLAM

extrinsic_calibration

Motion Based Multi-Sensor Extrinsic Calibration

fast-livo

A Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry.

fast-robust-icp

fast_gicp

A collection of GICP-based fast point cloud registration algorithms

fast_lio

A computationally efficient and robust LiDAR-inertial odometry (LIO) package

floam

Fast LOAM: Fast and Optimized Lidar Odometry And Mapping

gaussian-process-incremental-sample-consensus-gp-inasc

an implementation of GP-INSAC algorithm to achieve the driving region on 3D point clouds

gaussian-process-regression

Simple library with a basic no-frills implementation of GPR using Eigen. Basic support for multidimensional outputs.

glocal_exploration

Efficient local and global exploration on submap collections with changing past pose estimates.

gmmreg

Implementations of the robust point set registration algorithm described in "Robust Point Set Registration Using Gaussian Mixture Models", Bing Jian and Baba C. Vemuri, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(8), pp. 1633-1645. For a Python implementation, please refer to http://github.com/bing-jian/gmmreg-python.

gpr

Basic Gaussian process regression library. (Eigen3 required)

gpscalibration

GPS calibration using points cloud slam and other sensors

gpslam

Sparse Gaussian Processes for SLAM

ground-segmentation-for-lidar

This is ROS LiDAR ground segmation

groundsegmentationlidar16

GroundSegmentation using LiDAR16 PointCloud

gtsam

GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.

gtsam-examples

GTSAM Tutorial Examples

gvins

Tightly coupled GNSS-Visual-Inertial system for locally smooth and globally consistent state estimation in complex environment.

hand_eye_calibration

Python tools to perform time-synchronization and hand-eye calibration.

hand_eye_so4

The SO(4) solution to the hand-eye calibration problem AX = XB

handeyecat

easy, fast implementation of Tsai's hand-eye calibration algorithm