一、数据结构与算法（C++、python实现）
1.程序员小吴：https://github.com/MisterBooo/LeetCodeAnimation
2.star 58000星的python实现数据结构算法：https://github.com/TheAlgorithms/Python
3.又一个LeetCode题解：https://github.com/azl397985856/leetcode
4.图解算法的代码：https://github.com/egonSchiele/grokking_algorithms
5.数据结构与算法之美代码：https://github.com/wangzheng0822/algo
6.其实还是一个数据结构的资料，算是面试指南：https://github.com/kdn251/interviews
7.剑指offer源码：https://github.com/zhedahht/CodingInterviewChinese2
8.面试指南也是英文：https://github.com/jwasham/coding-interview-university
9.python100天：https://github.com/jackfrued/Python-100-Days
10.设计模式：https://github.com/guanguans/design-patterns-for-humans-cn
二、SLAM部分
1.贺一家的VINS课程代码：https://github.com/HeYijia/VINS-Course
2.SLAM各种资料链接汇总：https://github.com/JiaoYanMoGu/Bookmarks
3.东东师兄：https://github.com/wangzhaodong123/ORB_Segmentation
4.高翔的slambook：https://github.com/gaoxiang12/slambook https://github.com/gaoxiang12/slambook2
5.一个单目VO的例子：https://github.com/avisingh599/mono-vo
6.SLAM的一些开源介绍汇总：https://github.com/electech6/owesome-RGBD-SLAM
7.depth_segmention:https://github.com/ethz-asl/depth_segmentation
8.ORBSLAM2注释版：https://github.com/PaoPaoRobot/ORB_SLAM2
9.小觅相机：https://github.com/slightech/MYNT-EYE-VINS-Sample
10.vins代码学习：https://github.com/ManiiXu/VINS-Mono-Learning
11.VIORB：https://github.com/jingpang/LearnVIORB
12.vins-fusion：https://github.com/HKUST-Aerial-Robotics/VINS-Fusion
13.vins-mono：https://github.com/HKUST-Aerial-Robotics/VINS-Mono
14.msckf:https://github.com/KumarRobotics/msckf_vio
15.okvis:https://github.com/ethz-asl/okvis_ros
16.相机标定：https://github.com/ethz-asl/kalibr
17.泡泡机器人论文分享：https://github.com/PaoPaoRobot/SLAMPaperReading https://github.com/PaoPaoRobot/ICRA2019-paper-list https://github.com/extreme-assistant/cvpr2020
18.书的代码：https://github.com/AaronMR/Learning_ROS_for_Robotics_Programming_2nd_edition
19.graph_slam：https://github.com/rising-turtle/graph_slam
20.MTI驱动：https://github.com/lukscasanova/mtig_driver https://github.com/ethz-asl/ethzasl_xsens_driver https://github.com/xsens/xsens_mti_ros_node
21.DSO：https://github.com/JakobEngel/dso https://github.com/alalagong/DSO
22.SLAM中估算轨迹：https://github.com/uzh-rpg/rpg_trajectory_evaluation
三、ROS部分
1.白石的自主探索：https://github.com/RobustFieldAutonomyLab/turtlebot_exploration_3d
2.利用二维激光数据提取激光线段的新算法：https://github.com/ghm0819/laser-line-segment
3.ase_exploration：https://github.com/laurimi/ase_exploration
4.rviz中显示轨迹：https://github.com/HaoQChen/show_trajectory https://github.com/PickNikRobotics/rviz_visual_tools
5.teb_local_planner系列:https://github.com/rst-tu-dortmund/teb_local_planner_tutorials https://github.com/rst-tu-dortmund/teb_local_planner
6.同turtlebot差不多的小车：https://github.com/husky/husky
7.高翔的octomap教程：https://github.com/gaoxiang12/octomap_tutor
8.ROS入门实例的代码：https://github.com/pirobot/rbx1
9.分割合并算法：https://github.com/kam3k/laser_line_extraction
10.龙建全的RRT代码（RRT、RRT*、加贝塞尔曲线）：https://github.com/longjianquan/path-planning https://github.com/longjianquan/add--planner https://github.com/longjianquan/OMPL_ros_turtlebot
11.RRT有画板：https://github.com/jnez71/lqRRT
12.turtlebot_rrt：https://github.com/jeshoward/turtlebot_rrt
13.机器人跟随线 ：https://github.com/sudrag/line_follower_turtlebot
14.RRT探索：https://github.com/hasauino/rrt_exploration_tutorials https://github.com/hasauino/rrt_exploration
15.GeRoNa-通用机器人导航：https://github.com/cogsys-tuebingen/gerona
16.human_aware_navigation：https://github.com/marinaKollmitz/human_aware_navigation
17.spencer_people_tracking:https://github.com/spencer-project/spencer_people_tracking
18.前沿点探索：https://github.com/paulbovbel/frontier_exploration
19.应该是融合的东西：https://github.com/hiramzhang/gridmap_laser_rgbd_fusion https://github.com/robofit/but_sensor_fusion https://github.com/iralabdisco/ira_laser_tools
20.vision_opencv：https://github.com/ros-perception/vision_opencv
21.rtabmap好像不容易二次开发：https://github.com/introlab/rtabmap_ros
22.科大讯飞唤醒：https://github.com/HaoQChen/iflytek_awaken_asr
23.百度语音：https://github.com/DinnerHowe/baidu_speech
24.跟人走：https://github.com/TianyeAlex/tracker_kcf_ros
24.navigation：https://github.com/ros-planning/navigation
25.MTI和相机融合：https://github.com/MengxiaoChen/3D-mapping
26.robot_pose_ekf：https://github.com/udacity/robot_pose_ekf
27.提出了一些自主探索的概念：https://github.com/UbiCALab/cam_exploration
28.不太好用的自主探索：https://github.com/tyuownu/nearest_frontier_planner https://github.com/unr-arl/rhem_planner https://github.com/ethz-asl/nbvplanner https://github.com/hrnr/m-explore
29.泡泡机器人整理的：https://github.com/PaoPaoRobot/IROS2019-paper-list https://github.com/PaoPaoRobot/iros2018-slam-papers
30.IMU的包：https://github.com/gaowenliang/imu_utils
三、机器学习、深度学习部分
1.AI learning学习线路：https://github.com/apachecn/AiLearning
2.西瓜书笔记：https://github.com/Vay-keen/Machine-learning-learning-notes
3.强化学习：https://github.com/dennybritz/reinforcement-learning
4.黄海广博士：https://github.com/fengdu78
5.李宏毅机器学习笔记：https://github.com/datawhalechina/leeml-notes
6.深度学习500问：https://github.com/scutan90/DeepLearning-500-questions
7.TensorFlow Examples：https://github.com/aymericdamien/TensorFlow-Examples
8.吴恩达深度学习作业代码：https://github.com/greebear/deeplearning.ai-notes
9.numpy实现机器学习：https://github.com/ddbourgin/numpy-ml
10.tensorflow：https://github.com/tensorflow/tensorflow
11.动手学深度学习：https://github.com/d2l-ai/d2l-zh
12.南瓜书：https://github.com/datawhalechina/pumpkin-book
13.tensorflow中文版：https://github.com/jikexueyuanwiki/tensorflow-zh
14.TensorFlow学习：https://github.com/lawlite19/MachineLearning_TensorFlow
15.sklearn中文文档：https://github.com/apachecn/sklearn-doc-zh
16.CS229 课程讲义中文翻译：https://github.com/Kivy-CN/Stanford-CS-229-CN
17.吴恩达机器学习训练秘籍：https://github.com/deeplearning-ai/machine-learning-yearning-cn
四、其他