DB-PLPSlame's Stars
leekaka/V_SLAM
机器人视觉、移动机器人、跟踪、无人驾驶等
StevenCui/SLAMPaperReading
线下SLAM论文分享资料
lvhualong/classical-SLAM
一些经典的SLAM算法学习并注释的版本
saber/ORB_SLAM2_Notes
orb-slam2 开源代码学习笔记{问题解决集合、思路集合、学习资料整理、基本知识记录}
haocaichao/S-LOAM
S-LOAM(Simple LOAM) 是一种简单易学的激光SLAM算法,整个程序只有几百行代码,十分方便学习与试验分析。
gaoxiang12/slambook
Ewenwan/MVision
机器人视觉 移动机器人 VS-SLAM ORB-SLAM2 深度学习目标检测 yolov3 行为检测 opencv PCL 机器学习 无人驾驶
Krasjet/quaternion
A brief introduction to the quaternions and its applications in 3D geometry.
Lovely-XPP/Notebook
中山大学航空航天学院笔记
wuxiaolang/Visual_SLAM_Related_Research
视觉(语义) SLAM 相关研究跟踪
kongdaqing/SLAM-KDQ
slam相关学习资料
cggos/shenlan_vio_course
深蓝学院《视觉SLAM进阶:从零开始手写VIO》第一期
liulinbo/slam
learning SLAM,curse,paper and others
kahowang/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
electech6/LearnSLAM
SLAM研习社
electech6/ORB_SLAM3_detailed_comments
Detailed comments for ORB-SLAM3
yanyan-li/SLAM-BOOK
这是一本关于SLAM的书稿,希望能清楚的介绍SLAM系统中的使用的几何方法和深度学习方法。书稿最后应该会达到200页左右,书稿每章对应的代码也会被整理出来。
YiChenCityU/Recent_SLAM_Research
Track Advancement of SLAM 跟踪SLAM前沿动态【2021 version】業務調整,暫停更新
AlbertSlam/Lee-SLAM-source
SLAM 开发学习资源与经验分享
Ewenwan/ORB_SLAM2_SSD_Semantic
动态语义SLAM 目标检测+VSLAM+光流/多视角几何动态物体检测+octomap地图+目标数据库
raulmur/ORB_SLAM2
Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities
PaoPaoRobot/SLAMPaperReading
泡泡机器人北京线下SLAM论文分享资料
gaoxiang12/slambook2
edition 2 of the slambook
AlexanderDzhoganov/ksp-advanced-flybywire
Controller mod for Kerbal Space Program
saa1/sa
idawatibustan/uav_pathplanning
Implementation of path planning and trajectory algorithm for Unmanned Aerial Vehicle
Ankitvm/Coverage_Path_Planning-
This project aims at generating an optimal coverage planning algorithm based on linear sweep based decomposition - the algorithm uses pseudo-spectral optimal control to generate time-energy optimal trajectories for a given area in presence of obstacles.
YashTrikannad/apf_reactive_planning
Path Planning using Artificial Potential Fields
caokaifa/Matlab-planning
lalakaopu/multiagent-collision-avoidance