{"id":13414655,"url":"https://github.com/ahundt/awesome-robotics","last_synced_at":"2025-07-12T06:31:41.523Z","repository":{"id":38206506,"uuid":"91040492","full_name":"ahundt/awesome-robotics","owner":"ahundt","description":"A curated list of awesome links and software libraries that are useful for robots.","archived":false,"fork":false,"pushed_at":"2024-01-10T07:45:21.000Z","size":195,"stargazers_count":911,"open_issues_count":3,"forks_count":149,"subscribers_count":51,"default_branch":"master","last_synced_at":"2024-05-22T12:38:36.333Z","etag":null,"topics":["awesome","awesome-list","datasets","deep-learning","image-segmentation","list","lists","machine-learning","optimization","optimization-algorithms","physics","planning-algorithms","point-cloud","reinforcement-learning","robot","robotics","ros","sensors","simulation","tensorflow"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ahundt.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2017-05-12T01:58:27.000Z","updated_at":"2024-05-21T14:21:31.000Z","dependencies_parsed_at":"2024-01-13T21:23:19.705Z","dependency_job_id":null,"html_url":"https://github.com/ahundt/awesome-robotics","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahundt%2Fawesome-robotics","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahundt%2Fawesome-robotics/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahundt%2Fawesome-robotics/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahundt%2Fawesome-robotics/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ahundt","download_url":"https://codeload.github.com/ahundt/awesome-robotics/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":225800712,"owners_count":17526274,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["awesome","awesome-list","datasets","deep-learning","image-segmentation","list","lists","machine-learning","optimization","optimization-algorithms","physics","planning-algorithms","point-cloud","reinforcement-learning","robot","robotics","ros","sensors","simulation","tensorflow"],"created_at":"2024-07-30T21:00:32.107Z","updated_at":"2024-11-21T20:33:05.102Z","avatar_url":"https://github.com/ahundt.png","language":null,"funding_links":[],"categories":["Miscellaneous","Related lists","Related Awesome Lists","Uncategorized","Others","Other Lists","[Other Awesome Lists](#awesome-robotics-libraries)","[Relevant Awesome Lists](#contents)","硬件_其他","Related Lists","13.Other_Awesome_Topics","Related awesome lists ##","Awesome Robotics Lists"],"sub_categories":["Other lists","Deployment \u0026 DevEnv","Uncategorized","TeX Lists","[ETC](#awesome-robotics-libraries)","11. Cloth Simulation","资源传输下载","Mapping","Awesome Lists","Interest groups"],"readme":"# Awesome Robotics\n\n[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\n\nAwesome links, software libraries, [papers](papers.md), and other [intersting links](interesting.md) that are useful for robots.\n\n\nRelevant Awesome Lists\n----------------------\n\n- [Kiloreaux/awesome-robotics](https://github.com/Kiloreux/awesome-robotics) - Learn about Robotics.\n- [Robotics Libraries](https://github.com/jslee02/awesome-robotics-libraries) - Another list of awesome robotics libraries.\n- [Robotics Coursework](https://github.com/mithi/robotics-coursework) - A list of robotics courses you can take online\n- [Computer Vision](https://github.com/jbhuang0604/awesome-computer-vision)\n- [Deep Learning](https://github.com/ChristosChristofidis/awesome-deep-learning) - Neural networks.\n    - [TensorFlow](https://github.com/jtoy/awesome-tensorflow) - Library for machine intelligence.\n    - [Papers](https://github.com/terryum/awesome-deep-learning-papers) - The most cited deep learning papers.\n- [Deep Vision](https://github.com/kjw0612/awesome-deep-vision) - Deep learning for computer vision\n- [Data Visualization](https://github.com/fasouto/awesome-dataviz) - See what your robot is doing with any programming language.\n- [paperswithcode state of the art](https://paperswithcode.com/sota) - List of state of the art results on various machine learning benchmarks.\n\nSimulators\n----------\n\n- [CoppeliaSim](coppeliarobotics.com/index.html) - Create, Simulate, any Robot. (formerly named V-REP)\n- [Microsoft Airsim](https://github.com/Microsoft/AirSim) - Open source simulator based on Unreal Engine for autonomous vehicles from Microsoft AI \u0026 Research.\n- [Bullet Physics SDK](https://github.com/bulletphysics/bullet3) - Real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc. Also see [pybullet](https://pybullet.org).\n\nVisualization, Video, Display, and Rendering\n-----------------------\n\n - [Pangolin](https://github.com/stevenlovegrove/Pangolin) - A lightweight portable rapid development library for managing OpenGL display / interaction and abstracting video input.\n- [PlotJuggler](https://github.com/facontidavide/PlotJuggler) - Quickly plot and re-plot data on the fly! Includes optional ROS integration.\n- [Data Visualization](https://github.com/fasouto/awesome-dataviz) - A list of awesome data visualization tools.\n\nMachine Learning\n----------------\n\n### TensorFlow related\n\n- [Keras](https://keras.io) - Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano.\n- [keras-contrib](https://github.com/farizrahman4u/keras-contrib) - Keras community contributions.\n- [TensorFlow](tensorflow.org) - An open-source software library for Machine Intelligence.\n- [recurrentshop](https://github.com/datalogai/recurrentshop) - Framework for building complex recurrent neural networks with Keras.\n- [tensorpack](https://github.com/ppwwyyxx/tensorpack) - Neural Network Toolbox on TensorFlow.\n- [tensorlayer](https://github.com/zsdonghao/tensorlayer) - Deep Learning and Reinforcement Learning Library for Researchers and Engineers.\n- [TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples) - TensorFlow Tutorial and Examples for beginners.\n- [hyperas](https://github.com/maxpumperla/hyperas) - Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization.\n- [elephas](https://github.com/maxpumperla/elephas) - Distributed Deep learning with Keras \u0026 Spark\n- [PipelineAI](https://github.com/fluxcapacitor/pipeline) - End-to-End ML and AI Platform for Real-time Spark and Tensorflow Data Pipelines.\n- [sonnet](https://github.com/deepmind/sonnet) - Google Deepmind APIs on top of TensorFlow.\n- [visipedia/tfrecords](https://github.com/visipedia/tfrecords) - Demonstrates the use of TensorFlow's TFRecord data format.\n\n#### Image Segmentation\n\n- [tf-image-segmentation](https://github.com/warmspringwinds/tf-image-segmentation) - Image Segmentation framework based on Tensorflow and TF-Slim library.\n- [Keras-FCN](https://github.com/aurora95/Keras-FCN)\n\n\nLogging and Messaging\n---------------------\n\n- [spdlog](https://github.com/gabime/spdlog) - Super fast C++ logging library.\n- [lcm](https://github.com/lcm-proj/lcm) - Lightweight Communications and Marshalling, message passing and data marshalling for real-time systems where high-bandwidth and low latency are critical.\n\nTracking\n--------\n\n- [simtrack](https://github.com/karlpauwels/simtrack) - A simulation-based framework for tracking.\n- [ar_track_alvar](https://github.com/sniekum/ar_track_alvar) - AR tag tracking library for ROS.\n- [artoolkit5](https://github.com/artoolkit/artoolkit5) - Augmented Reality Toolkit, which has excellent AR tag tracking software.\n\nRobot Operating System (ROS)\n----------------------------\n\n- [ROS](ros.org) - Main ROS website.\n- [ros2/design](https://github.com/ros2/design) - Design documentation for ROS 2.0 effort.\n\n\nKinematics, Dynamics, Constrained Optimization\n----------------------------------------------\n\n- [jrl-umi3218/Tasks](https://github.com/jrl-umi3218/Tasks) - Tasks is library for real time control of robots and kinematic trees using constrained optimization.\n- [jrl-umi3218/RBDyn](https://github.com/jrl-umi3218/RBDyn) - RBDyn provides a set of classes and functions to model the dynamics of rigid body systems.\n- [ceres-solver](https://github.com/ceres-solver/ceres-solver) - Solve Non-linear Least Squares problems with bounds constraints and general unconstrained optimization problems. Used in production at Google since 2010.\n- [orocos_kinematics_dynamics](https://github.com/orocos/orocos_kinematics_dynamics) - Orocos Kinematics and Dynamics C++ library.\n- [flexible-collsion-library](https://github.com/flexible-collision-library/fcl) - Performs three types of proximity queries on a pair of geometric models composed of triangles, integrated with ROS. \n- [robot_calibration](https://github.com/mikeferguson/robot_calibration) - generic robot kinematics calibration for ROS\n- [ruckig](https://github.com/pantor/ruckig) - Real-time, time-optimal and jerk-constrained online trajectory generation.\n\nCalibration\n-----------\n\n- [handeye-calib-camodocal](https://github.com/jhu-lcsr/handeye_calib_camodocal) - generic robot hand-eye calibration.\n- [robot_calibration](https://github.com/mikeferguson/robot_calibration) - generic robot kinematics calibration for ROS\n- [kalibr](https://github.com/ethz-asl/kalibr) - camera and imu calibration for ROS\n\nReinforcement Learning\n----------------------\n\n- [\"Good Robot!\": Efficient Reinforcement Learning for Multi-Step Visual Tasks with Sim to Real Transfer](https://github.com/jhu-lcsr/good_robot) - A real robot completes multi-step tasks after \u003c20k simulated actions. [Good Robot on ArXiV](https://arxiv.org/abs/1909.11730) (disclaimer: @ahundt is first author)\n- [TensorForce](https://github.com/reinforceio/tensorforce) - A TensorFlow library for applied reinforcement learning\n- [gqcnn](https://github.com/BerkeleyAutomation/gqcnn) -  [Grasp Quality Convolutional Neural Networks (GQ-CNNs)](https://berkeleyautomation.github.io/gqcnn/info/info.html) for grasp planning using training datasets from the [Dexterity Network (Dex-Net)](https://berkeleyautomation.github.io/dex-net)\n- [Guided Policy Search](https://github.com/cbfinn/gps) - Guided policy search (gps) algorithm and LQG-based trajectory optimization, meant to help others understand, reuse, and build upon existing work. \n\nDrivers for Sensors, Devices and Arms\n-------------------------------------\n\n- [libfreenect2](https://github.com/OpenKinect/libfreenect2) - Open source drivers for the Kinect for Windows v2 and Xbox One devices.\n- [iai_kinect2](https://github.com/code-iai/iai_kinect2) - Tools for using the Kinect One (Kinect v2) in ROS.\n- [grl](https://github.com/ahundt/grl) - Generic Robotics Library: Cross platform drivers for Kuka iiwa and Atracsys FusionTrack with optional v-rep and ros drivers. Also has cross platform Hand Eye Calibration and Tool Tip Calibration.\n\nDatasets\n--------\n\n- [CoSTAR Block Stacking Dataset](https://sites.google.com/site/costardataset) - Robot stacking colored children's blocks (disclaimer: created by @ahundt)\n- [shapestacks](http://shapestacks.robots.ox.ac.uk/#paper) - simulated stacks of colored children's objects\n- [pascal voc 2012](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/) - The classic reference image segmentation dataset.\n- [openimages](https://github.com/openimages/dataset/) - Huge imagenet style dataset by Google.\n- [COCO](mscoco.org) - Objects with segmentation, keypoints, and links to many other external datasets.\n- [cocostuff](https://github.com/nightrome/cocostuff) - COCO additional full scene segmentation including backgrounds and annotator.\n- [Google Brain Robot Data](https://sites.google.com/site/brainrobotdata/home) - Robotics datasets including grasping, pushing, and pouring.\n- [Materials in Context](http://opensurfaces.cs.cornell.edu/publications/minc/) - Materials Dataset with real world images in 23 categories.\n- [Dex-Net 2.0](http://bair.berkeley.edu/blog/2017/06/27/dexnet-2.0/) - 6.7 million pairs of synthetic point clouds and grasps with robustness labels.\n\n#### Dataset Collection\n- [LabelFusion](labelfusion.csail.mit.edu) - \"A Pipeline for Generating Ground Truth Labels for Real RGBD Data of Cluttered Scenes\" [code](https://github.com/RobotLocomotion/LabelFusion)\n- [cocostuff](https://github.com/nightrome/cocostuff) - COCO additional full scene segmentation including backgrounds and annotator.\n\nLinear Algebra \u0026 Geometry\n-------------------------\n\n- [Eigen](http://eigen.tuxfamily.org) - Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms.\n- [Boost.QVM](https://github.com/boostorg/qvm) - Quaternions, Vectors, Matrices library for Boost.\n- [Boost.Geometry](https://github.com/boostorg/geometry/) - Boost.Geometry contains instantiable geometry classes, but library users can also use their own.\n- [SpaceVecAlg](https://github.com/jrl-umi3218/SpaceVecAlg) - Implementation of spatial vector algebra for 3D geometry with the Eigen3 linear algebra library.\n- [Sophus](https://github.com/strasdat/Sophus) - C++ implementation of Lie Groups which are for 3D Geometry, using Eigen.\n\n\nPoint Clouds\n------------\n\n- [libpointmatcher](https://github.com/ethz-asl/libpointmatcher) - An \"Iterative Closest Point\" library robotics and 2-D/3-D mapping.\n- [Point Cloud Library (pcl)](https://github.com/PointCloudLibrary/pcl) - The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing.\n\n\n\nSimultaneous Localization and Mapping (SLAM)\n--------------------------------------------\n\n- [ElasticFusion](https://github.com/mp3guy/ElasticFusion) - Real-time dense visual SLAM system.\n- [co-fusion](https://github.com/martinruenz/co-fusion) - Real-time Segmentation, Tracking and Fusion of Multiple Objects. Extends ElasticFusion.\n- [Google Cartographer](https://github.com/googlecartographer/cartographer/) - Cartographer is a system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations.\n- [OctoMap](https://github.com/OctoMap/octomap) - An Efficient Probabilistic 3D Mapping Framework Based on Octrees. Contains the main OctoMap library, the viewer octovis, and dynamicEDT3D.\n- [ORB_SLAM2](https://github.com/raulmur/ORB_SLAM2) - Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities.\n\n\n# License\n\n\u003ca rel=\"license\" href=\"http://creativecommons.org/licenses/by/4.0/\"\u003e\u003cimg alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by/4.0/88x31.png\" /\u003e\u003c/a\u003e\u003cbr /\u003eThis work is licensed under a \u003ca rel=\"license\" href=\"http://creativecommons.org/licenses/by/4.0/\"\u003eCreative Commons Attribution 4.0 International License\u003c/a\u003e.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fahundt%2Fawesome-robotics","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fahundt%2Fawesome-robotics","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fahundt%2Fawesome-robotics/lists"}