LiuHahahaha

LiuHahahaha's Stars

• LTU-RAI/traversability_mapping

  Language:C++1

• TixiaoShan/traversability_mapping

  Bayesian Generalized Kernel Inference for Terrain Traversability Mapping

  Language:C++25864

• ctu-vras/traversability_estimation

  Semantic Segmentation of Images and Point Clouds for Traversability Estimation

  Language:Python386

• suyunzzz/ray_filter_ground

  Language:C++153

• jkk-research/urban_road_filter

  Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles 🚗

  Language:C++28678

• abeleinin/gp-navigation

  Gaussian Process-based Traversability Analysis for Terrain Mapless Navigation

  Language:Python472

• LiZhengXiao99/Navigation-Learning

  我的导航学习笔记，内容涵盖导航定位开源程序的源码解读 ( 包括：RTKLIB、GAMP、GINav、Ginan、PSINS、SoftGNSS、KF-GINS、ORB-SLAM3、GICI-Lib 等)、各种导航设备的使用方式、书籍讲义、博客翻译、开源项目梳理、常用网站记录、Linux/Vim/Git/ROS/VSCode 常用命令；本仓库会长期更新，分享出来，跟大家做个交流，也激励着自己坚持学下去；所有内容都可以随意转载，可用于任何目的，不必征求我的意见；如果您觉得内容有价值，推荐用 Github-Desktop 下载并保持更新。

  Language:Python856208

• liyang-whu/lidar_rtk_calibration

  使用手眼标定法计算Lidar和INS(RTK or IMU)的相对姿态

  11831

• Ikhyeon-Cho/height_mapping

  Range sensor-based 2.5D gridded height mapping (Digital Elevation Model) for urban terrain navigation of mobile robots

  Language:C++172

• imarvinle/interview-1

  📚 C/C++面试知识总结

  Language:C++28759

• Light-City/CPlusPlusThings

  C++那些事

  Language:C++38.6k8.4k

• liuqian62/notebook

  记笔记，包括c++学习，slam学习，面经八股文

  9213

• zhaohaowu/localzation_mapping_navigation

  Language:C++346

• linyicheng1/laser_localization

  laser localization base global map for robotics

  Language:C++238

• CentroEPiaggio/lidar_based_map_updating

  Ros-Packages to update an occupancy grid map with lidar measurements.

  Language:C++2313

• ZrrSkywalker/Point-NN

  [CVPR 2023] Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis

  Language:Python47149

• thejeffreyli/point-cloud-classification-exploration

  Advanced Machine Perception (Fall 2023) Group Project. Exploration of PointNet and PointNN architectures. Special thanks to Ning-Yuan and Professor Shi!

  Language:Jupyter Notebook31

• DLonng/RSPMP

  RSPMP: real-time semantic perception and motion planning for autonomous navigation of unmanned ground vehicle in off-road environments

  Language:C++508

• HKUST-Aerial-Robotics/open_quadtree_mapping

  This is a monocular dense mapping system corresponding to IROS 2018 "Quadtree-accelerated Real-time Monocular Dense Mapping"

  Language:Cuda35687

• biter0088/Non-uniform-quadtree-map

  A Non-Uniform Quadtree Map Building Method Including Dead-End Semantics Extraction

  Language:C++492

• ANYbotics/elevation_mapping

  Robot-centric elevation mapping for rough terrain navigation

  Language:C++1.3k442

• ANYbotics/grid_map

  Universal grid map library for mobile robotic mapping

  Language:C++2.6k798

• ethz-asl/grid_map

  Universal grid map library for mobile robotic mapping

  Language:C++32

• dcmlr/groundgrid

  Source code for the article "GroundGrid: LiDAR Point Cloud Ground Segmentation and Terrain Estimation"

  Language:C++12512

• jkk-research/pointcloud_to_grid

  ROS 1 and ROS 2 node that converts sensor_msgs/PointCloud2 LIDAR data to nav_msgs/OccupancyGrid 2D map data based on intensity and / or height. 🤖

  Language:C++498

• HMX2013/CVC-ROS

  An ROS implementation for paper "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance"

  Language:C++274

• wangx1996/Lidar-Segementation

  An implementation on "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance" from IROS 2019

  Language:C++22145

• Nisarg236/traversable_area_from_pt_clouds

  This package is used to segment traversable areas from a point cloud.

  Language:C++31

• url-kaist/TRAVEL

  Traversable ground and above-ground object segmentation using graph representation of 3D LiDAR scans

  Language:C++24927

• chenyirui/FASTC

  Code repository for “FASTC: A Fast Attentional Framework for Semantic Traversability Classification Using Point Cloud“

  Language:Python4