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List of open-source algorithms and resources for autonomous drones. The list is a work in progress! |
Link | Who | Description | ROS |
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visual-slam-roadmap | Great Roadmap for Visual SLAM | ||
voxblox | ETH | voxel-based mapping | ✔️ |
maplab | ETH | visual inertial mapping | ✔️ |
orb-slam2 | sparse 3D reconstruction | ✔️ | |
open_vins | U. of Delaware | EKF fuses inertial info with sparse visual features | ✔️ |
SVO 2.0 | ETH | semi-direct paradigm to estimate pose from pixel intensities and features | ✔️ |
DSO | TUM | direct sparse odometry | |
XIVO | UCLA | inertial-aided visual odometry | |
VINS-Fusion | HKUST | An optimization-based multi-sensor state estimator | |
Kimera-VIO | MIT | real-time metric-semantic SLAM and VIO | ✔️ |
tagSLAM | UPenn | tagSLAM with apriltags | ✔️ |
LARVIO | A lightweight, accurate and robust monocular visual inertial odometry based on Multi-State Constraint Kalman Filter. | ✔️ | |
R-VIO | based on robocentric sliding-window filtering-based VIO framework | ||
nanomap | MIT | fast, uncertainty-aware proximity queries with lazy search of local 3D data | |
MSCKF_VIO | UPenn | package is a stereo version of MSCKF | |
VINS_mono | HKUST | Robust and Versatile Monocular Visual-Inertial State Estimator | |
SLAM_toolbox | Simbe Robotics / Samsung Research | SLAM for massive maps | ✔️ |
Link | Who | Description | ROS |
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mav_trajectory_generation | ETH | creates polynomial path | ✔️ |
mav_voxblox_planning | ETH | planning tool using voxblox (RRT*, etc.) | ✔️ |
pulp-dronet | ETH | deep learning visual navigation | |
Ewok: real-time traj replanning | TUM | replanning of global traj, needs prior map | |
Deep RL with Transfer Learning | Georgia Tech | end-to-end navigation trained from simulation | |
NVIDIA redtail project | Autonomous navigation for drones | ||
Fast-Planner | HKUST | robust and efficient trajectory planner for quads | ✔️ |
ego-planner swarm | Zhejiang University | Autonomous and Decentralized Quadrotor Swarm System in Cluttered Environments | |
spatio-temporal semantic corridor | HKUST | Safe Trajectory Generation For Complex Urban Environments Using Spatio-temporal Semantic Corridor | |
EVDodgeNet | ETH | obstacle avoidance with event cameras | |
aeplanner | KTH | unknown environment exploration based on octomap | |
nvbplanner | ETH | unknown environment exploration | |
HKUST Aerial Robotics | HKUST | a complete and robust system for aggressive flight in complex environment | |
sim2real_drone_racing | ETH | deep learning Sim2Real Drone racing | ✔️ |
waypoint_navigator | ETH | high-level waypoint-following for micro aerial vehicles | ✔️ |
toppra | Eureka Robotics | Time-Optimal Path Parameterization |
Link | Who | Description | ROS |
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neural_mpc | Berkeley | Model Predictive Control with one-step feedforward neural network dynamics model from Model-based Reinforcement Learning | |
Control Toolbox | ETH | efficient C++ library for control, estimation, optimization and motion planning in robotics | |
PythonLinearNonlinearControl | library implementing the linear and nonlinear control theories in python | ||
rpg_mpc | ETH | Model Predictive Control for Quadrotors with extension to Perception-Aware MPC | |
rpg_quadrotor_control | ETH | alternative to PX4 that works with RotorS | |
gymFC | flight control tuning framework with a focus in attitude control | ||
ACADO toolkit | MPC toolkit that takes care of the implementation | ||
MPC ETH | ETH | also has PX4 implementation (claim badly hacked though) | |
DDC-MPC | ETH | Data-Driven MPC for Quadrotors | |
Deep-drone acrobatics | ETH | fly complex maneuvers with multi-layer perceptron | |
mav_control_rw | ETH | trajectory tracking with MPC | |
rpg_quadrotor_control | ETH | complete framework for flying quadrotors | |
flight controller | HKUST | high level controller compatible with DJI N3 flight controller | |
mavros_trajectory_tracking | combines mav_trajectory_generation and waypoint_navigator with mavros_controller | ✔️ | |
system identification scripts | ETH | calculates model parameters for a drone | |
MRS UAV framework | CTU | framework for controlling drones with PX4 and different advanced controllers |
Lab Website | Git | Where |
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Robotics & Perception Group | Link | Zurich, Switzerland |
GRASP Lab | Link | Philadelphia, USA |
ZJU FAST Lab | Link | Hangzhou, China |
HKUST Aerial Robotics Group | Link | Clear Water Bay, Hong Kong |
Team Aerial Robotics IIT Kanpur | Link | Kanpur, India |