Pinned Repositories
AVP-SLAM-PLUS
An implementation of AVP-SLAM and some new contributions
dbscan_kdtree
Fast Implementation of DBSCAN using Kdtree for acceleration. The example is clustering point cloud(PCL library used).
DRL-robot-navigation
Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.
DynamicMap_Benchmark
[ITSC'23] Dynamic map benchmark, open-sourced all the methods and datasets in the paper.
ERASOR
Official page of ERASOR (Egocentric Ratio of pSeudo Occupancy-based Dynamic Object Removal), which is accepted @ RA-L'21 with ICRA'21
ERASOR2
[RSS'23] The official Implementation of "ERASOR2: Instance-Aware Robust 3D Mapping of the Static World in Dynamic Scenes"
ground_aware_cartographer
添加了地面约束的3D版本Cartographer，更多改进详见readme。
hdl_graph_slam
3D LIDAR-based Graph SLAM
LIO-SAM
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
LIO-SAM-MID360
Jun-creat's Repositories
Jun-creat/AVP-SLAM-PLUS
An implementation of AVP-SLAM and some new contributions
Jun-creat/dbscan_kdtree
Fast Implementation of DBSCAN using Kdtree for acceleration. The example is clustering point cloud(PCL library used).
Jun-creat/DRL-robot-navigation
Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.
Jun-creat/DynamicMap_Benchmark
[ITSC'23] Dynamic map benchmark, open-sourced all the methods and datasets in the paper.
Jun-creat/ERASOR
Official page of ERASOR (Egocentric Ratio of pSeudo Occupancy-based Dynamic Object Removal), which is accepted @ RA-L'21 with ICRA'21
Jun-creat/ERASOR2
[RSS'23] The official Implementation of "ERASOR2: Instance-Aware Robust 3D Mapping of the Static World in Dynamic Scenes"
Jun-creat/ground_aware_cartographer
添加了地面约束的3D版本Cartographer，更多改进详见readme。
Jun-creat/hdl_graph_slam
3D LIDAR-based Graph SLAM
Jun-creat/LIO-SAM
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
Jun-creat/LIO-SAM-MID360
Jun-creat/LIO-SAM_based_relocalization
A simple system that can relocalize a robot on a built map is developed in this system. The system is based on LIO-SAM.
Jun-creat/LIOSAM-corlor
Jun-creat/M2DGR-plus
Extension and update of M2DGR: a novel Multi-modal and Multi-scenario SLAM Dataset for Ground Robots (ICRA2022 & ICRA2024)
Jun-creat/NEXTE_Sentry_Nav
The navigation system of "sentry" for Next-E team in RoboMaster2023
Jun-creat/octomap
An Efficient Probabilistic 3D Mapping Framework Based on Octrees. Contains the main OctoMap library, the viewer octovis, and dynamicEDT3D.
Jun-creat/patchwork
SOTA fast and robust ground segmentation using 3D point cloud (accepted in RA-L'21 w/ IROS'21)
Jun-creat/SC-LIO-SAM
LiDAR-inertial SLAM: Scan Context + LIO-SAM
Jun-creat/semantic-kitti-api
SemanticKITTI API for visualizing dataset, processing data, and evaluating results.
Jun-creat/sensor-fusion-for-localization-and-mapping
深蓝学院 多传感器定位融合第四期 学习笔记
Jun-creat/slam_in_autonomous_driving
《自动驾驶中的SLAM技术》对应开源代码
Jun-creat/TRAVEL
Traversable ground and above-ground object segmentation using graph representation of 3D LiDAR scans
Jun-creat/UrbanLoco
UrbanLoco: A Full Sensor Suite Dataset for Mapping and Localization in Urban Scenes
Jun-creat/UrbanNavDataset
UrbanNav:An Open-sourced Multisensory Dataset for Benchmarking Positioning Algorithms Designed for Urban Areas
Jun-creat/Yolov5-deepsort-inference
Yolov5 deepsort inference，使用YOLOv5+Deepsort实现车辆行人追踪和计数，代码封装成一个Detector类，更容易嵌入到自己的项目中
Jun-creat/Yolov5_ros
Real-time object detection with ROS, based on YOLOv5 and PyTorch (基于 YOLOv5的ROS实时对象检测)