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Xu Shengpan's Projects

a-loam icon a-loam

Advanced implementation of LOAM

avp-slam-plus icon avp-slam-plus

An implementation of AVP-SLAM and some new contributions, for parking.

cartographer icon cartographer

Cartographer is a system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations.

eskf icon eskf

An implementation of an Error State Kalman Filter (ESKF)

eskf_lio icon eskf_lio

IESKF-LIO reference to fast_lio1.0(参考fast-lio早期版本,复现的fast-lio2)

fast-gicp icon fast-gicp

fast-gicp包含了ndt_cuda,fast-gicp,fast-vgicp

faster-lio icon faster-lio

Faster-LIO: Lightweight Tightly Coupled Lidar-inertial Odometry using Parallel Sparse Incremental Voxels

gtsam icon 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.

gvins icon gvins

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

imu_ekf icon imu_ekf

A ROS C++ node that fuses IMU and Odometry

laslib icon laslib

LAS file reader/writer mainly for LAS 1.2.

lego-loam icon lego-loam

LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain

lidar_align icon lidar_align

A simple method for finding the extrinsic calibration between a 3D lidar and a 6-dof pose sensor

lins---lidar-inertial-slam icon lins---lidar-inertial-slam

A Lidar-Inertial State Estimator for Robust and Efficient Navigation based on iterated error-state Kalman filter

lio-mapping icon lio-mapping

Implementation of Tightly Coupled 3D Lidar Inertial Odometry and Mapping (LIO-mapping)

lio-sam icon lio-sam

LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping

loam_livox icon loam_livox

A robust LiDAR Odometry and Mapping (LOAM) package for Livox-LiDAR

mpcdps icon mpcdps

A c++ library which aims at massive point cloud data processing, involves smart pointer and smart array, mathematical structures and operations(vector, matrix, quaternion, transform etc), computational geometry(point, line, plane, polygon, rect, box, convex hull etc) indices (grid, kd-tree, octree, r-tree) and clusters (distance cluster, DBScan cluster, mean-shift cluster) etc.

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