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| --- | ||
| description: >- | ||
| List of open-source algorithms and resources for autonomous drones. The list | ||
| is a work in progress! | ||
| --- | ||
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| # Open-source algorithms and resources | ||
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| ### Perception | ||
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| | Link | Who | Description | ROS | | ||
| | ---------------------------------------------------------------------- | --------------------------------- | -------------------------------------------------------------------------------------------------------------------- | -------------------- | | ||
| | [visual-slam-roadmap](https://github.com/changh95/visual-slam-roadmap) | | Great Roadmap for Visual SLAM | | | ||
| | [voxblox](https://github.com/ethz-asl/voxblox) | ETH | voxel-based mapping | :heavy\_check\_mark: | | ||
| | [maplab](https://github.com/ethz-asl/mav\_voxblox\_planning) | ETH | visual inertial mapping | :heavy\_check\_mark: | | ||
| | [orb-slam2](https://github.com/raulmur/ORB\_SLAM2) | | sparse 3D reconstruction | :heavy\_check\_mark: | | ||
| | [open\_vins](https://github.com/rpng/open\_vins) | U. of Delaware | EKF fuses inertial info with sparse visual features | :heavy\_check\_mark: | | ||
| | [SVO 2.0](http://rpg.ifi.uzh.ch/svo2.html) | ETH | semi-direct paradigm to estimate pose from pixel intensities and features | :heavy\_check\_mark: | | ||
| | [DSO](https://github.com/JakobEngel/dso/) | TUM | direct sparse odometry | | | ||
| | [XIVO](https://feixh.github.io/projects/xivo/) | UCLA | inertial-aided visual odometry | | | ||
| | [VINS-Fusion](https://github.com/HKUST-Aerial-Robotics/VINS-Fusion) | HKUST | An optimization-based multi-sensor state estimator | | | ||
| | [Kimera-VIO](https://github.com/MIT-SPARK/Kimera) | MIT | real-time metric-semantic SLAM and VIO | :heavy\_check\_mark: | | ||
| | [tagSLAM](https://github.com/berndpfrommer/tagslam) | UPenn | tagSLAM with apriltags | :heavy\_check\_mark: | | ||
| | [LARVIO](https://github.com/PetWorm/LARVIO) | | A lightweight, accurate and robust monocular visual inertial odometry based on Multi-State Constraint Kalman Filter. | :heavy\_check\_mark: | | ||
| | [R-VIO](https://github.com/rpng/R-VIO) | | based on robocentric sliding-window filtering-based VIO framework | | | ||
| | [nanomap](https://github.com/peteflorence/nanomap\_ros) | MIT | fast, uncertainty-aware proximity queries with lazy search of local 3D data | | | ||
| | [MSCKF\_VIO](https://github.com/KumarRobotics/msckf\_vio) | UPenn | package is a stereo version of MSCKF | | | ||
| | [VINS\_mono](https://github.com/HKUST-Aerial-Robotics/VINS-Mono) | HKUST | Robust and Versatile Monocular Visual-Inertial State Estimator | | | ||
| | [SLAM\_toolbox](https://github.com/SteveMacenski/slam\_toolbox) | Simbe Robotics / Samsung Research | SLAM for massive maps | :heavy\_check\_mark: | | ||
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| ### Navigation | ||
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| | Link | Who | Description | ROS | | ||
| | ---------------------------------------------------------------------------------------------------------------- | ------------------- | ------------------------------------------------------------------------------------------------- | -------------------- | | ||
| | [mav\_trajectory\_generation](https://github.com/ethz-asl/mav\_trajectory\_generation) | ETH | creates polynomial path | :heavy\_check\_mark: | | ||
| | [mav\_voxblox\_planning](https://github.com/ethz-asl/mav\_voxblox\_planning) | ETH | planning tool using voxblox (RRT\*, etc.) | :heavy\_check\_mark: | | ||
| | [pulp-dronet](https://github.com/pulp-platform/pulp-dronet) | ETH | deep learning visual navigation | | | ||
| | [Ewok: real-time traj replanning](https://github.com/VladyslavUsenko/ewok) | TUM | replanning of global traj, needs prior map | | | ||
| | [Deep RL with Transfer Learning](https://github.com/aqeelanwar/DRLwithTL\_real) | Georgia Tech | end-to-end navigation trained from simulation | | | ||
| | [NVIDIA redtail project](https://github.com/NVIDIA-AI-IOT/redtail) | | Autonomous navigation for drones | | | ||
| | [Fast-Planner](https://github.com/HKUST-Aerial-Robotics/Fast-Planner) | HKUST | robust and efficient trajectory planner for quads | :heavy\_check\_mark: | | ||
| | [ego-planner swarm](https://github.com/ZJU-FAST-Lab/ego-planner-swarm) | Zhejiang University | Autonomous and Decentralized Quadrotor Swarm System in Cluttered Environments | | | ||
| | [spatio-temporal semantic corridor](https://github.com/HKUST-Aerial-Robotics/spatiotemporal\_semantic\_corridor) | HKUST | Safe Trajectory Generation For Complex Urban Environments Using Spatio-temporal Semantic Corridor | | | ||
| | [EVDodgeNet](https://github.com/prgumd/EVDodgeNet) | ETH | obstacle avoidance with event cameras | | | ||
| | [aeplanner](https://github.com/mseln/aeplanner) | KTH | unknown environment exploration based on octomap | | | ||
| | [nvbplanner](https://github.com/ethz-asl/nbvplanner) | ETH | unknown environment exploration | | | ||
| | [HKUST Aerial Robotics](https://github.com/HKUST-Aerial-Robotics/Teach-Repeat-Replan) | HKUST | a complete and robust system for aggressive flight in complex environment | | | ||
| | [sim2real\_drone\_racing](https://github.com/uzh-rpg/sim2real\_drone\_racing) | ETH | deep learning Sim2Real Drone racing | :heavy\_check\_mark: | | ||
| | [waypoint\_navigator](https://github.com/ethz-asl/waypoint\_navigator) | ETH | high-level waypoint-following for micro aerial vehicles | :heavy\_check\_mark: | | ||
| | [toppra](https://github.com/hungpham2511/toppra) | Eureka Robotics | Time-Optimal Path Parameterization | | | ||
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| ### Controls | ||
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| | Link | Who | Description | ROS | | ||
| | ------------------------------------------------------------------------------------------------------------------------------------- | -------- | ------------------------------------------------------------------------------------------------------------------------ | -------------------- | | ||
| | [neural\_mpc](https://github.com/aravindsrinivas/neural-mpc) | Berkeley | Model Predictive Control with one-step feedforward neural network dynamics model from Model-based Reinforcement Learning | | | ||
| | [Control Toolbox](https://github.com/ethz-adrl/control-toolbox) | ETH | efficient C++ library for control, estimation, optimization and motion planning in robotics | | | ||
| | [PythonLinearNonlinearControl](https://github.com/Shunichi09/PythonLinearNonlinearControl) | | library implementing the linear and nonlinear control theories in python | | | ||
| | [rpg\_mpc](https://github.com/uzh-rpg/rpg\_mpc) | ETH | Model Predictive Control for Quadrotors with extension to Perception-Aware MPC | | | ||
| | [rpg\_quadrotor\_control](https://github.com/uzh-rpg/rpg\_quadrotor\_control) | ETH | alternative to PX4 that works with RotorS | | | ||
| | [gymFC](https://github.com/wil3/gymfc) | | flight control tuning framework with a focus in attitude control | | | ||
| | [ACADO toolkit](http://acado.github.io/index.html) | | MPC toolkit that takes care of the implementation | | | ||
| | [MPC ETH](https://github.com/ethz-asl/mav\_control\_rw) | ETH | also has PX4 implementation (claim badly hacked though) | | | ||
| | [DDC-MPC](https://github.com/uzh-rpg/data\_driven\_mpc) | ETH | Data-Driven MPC for Quadrotors | | | ||
| | [Deep-drone acrobatics](https://github.com/uzh-rpg/deep\_drone\_acrobatics) | ETH | fly complex maneuvers with multi-layer perceptron | | | ||
| | [mav\_control\_rw](https://github.com/ethz-asl/mav\_control\_rw) | ETH | trajectory tracking with MPC | | | ||
| | [rpg\_quadrotor\_control](https://github.com/uzh-rpg/rpg\_quadrotor\_control) | ETH | complete framework for flying quadrotors | | | ||
| | [flight controller](https://github.com/HKUST-Aerial-Robotics/Teach-Repeat-Replan/tree/experiment/onboard\_computer/controller/n3ctrl) | HKUST | high level controller compatible with DJI N3 flight controller | | | ||
| | [mavros\_trajectory\_tracking](https://github.com/mzahana/mavros\_trajectory\_tracking) | | combines mav\_trajectory\_generation and waypoint\_navigator with mavros\_controller | :heavy\_check\_mark: | | ||
| | [system identification scripts](https://github.com/ethz-asl/mav\_system\_identification) | ETH | calculates model parameters for a drone | | | ||
| | [MRS UAV framework](https://github.com/ctu-mrs/mrs\_uav\_system) | CTU | framework for controlling drones with PX4 and different advanced controllers | | | ||
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| ### Labs/Organizations to follow | ||
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| | Lab Website | Git | Where | | ||
| | ----------------------------------------------------- | ------------------------------------------------ | -------------------------- | | ||
| | [Robotics & Perception Group](http://rpg.ifi.uzh.ch/) | [Link](https://github.com/uzh-rpg) | Zurich, Switzerland | | ||
| | [GRASP Lab](https://www.kumarrobotics.org/) | [Link](https://github.com/KumarRobotics) | Philadelphia, USA | | ||
| | [ZJU FAST Lab](http://zju-fast.com/) | [Link](https://github.com/ZJU-FAST-Lab) | Hangzhou, China | | ||
| | [HKUST Aerial Robotics Group](http://uav.ust.hk/) | [Link](https://github.com/HKUST-Aerial-Robotics) | Clear Water Bay, Hong Kong | | ||
| | [Team Aerial Robotics IIT Kanpur](http://ariitk.in/) | [Link](https://github.com/AerialRobotics-IITK) | Kanpur, India | |