All papers and resources related to Quadrotor Research.
- Our own CMSC828T course
- Vijay Kumar's UPenn course
- Daniel Mellinger's Thesis
- UZH's Quadrotor Tutorial
- Minimum Snap Trajectory: Kumar's Minimum Snap trajectory generator. Code
- Polynomial trajectory planning for aggressive quadrotor flight in dense indoor environments: Nicholas Roy's MIT trajectory generator. Code
- A computationally efficient motion primitive for quadrocopter trajectory generation: Raffaello D’Andrea's trajectory generator. Code
- Search-based Motion Planning for Aggressive Flight in SE(3): Kumar's aggressive motion planning, can go through a forest aggressively. Code
- Design of Decoupling and Nonlinear PD Controller for Cruise Control of a Quadrotor. Aug 2017.
- Modelling and control of quadcopter, Teppo Luukkonen. (2011)
- Aggressive Quadrotor Flight through Narrow Gaps with Onboard Sensing and Computing using Active Vision, Falanga, David Scaramuzza et al, (ICRA 2017). Supplementary video
- N. Michael, D. Mellinger, Q. Lindsey, and V. Kumar, “The GRASP multiple micro UAV testbed,” IEEE Robot. Autom. Mag., vol. 17, no. 3, pp. 56–65, Sep. 2010.
- M. Faessler, F. Fontana, C. Forster, and D. Scaramuzza, “Automatic reinitialization and failure recovery for aggressive flight with a monocular vision-based quadrotor,” in Proc. IEEE Int. Conf. Robot. Autom., 2015, pp. 1722–1729.
- D. Mellinger, N. Michael, and V. Kumar, “Trajectory generation and control for precise aggressive maneuvers with quadrotors,” Int. J. Robot. Res., vol. 31, no. 5, pp. 664–674, 2012.
- M. Hehn and R. D’Andrea, “A frequency domain iterative learning algorithm for high-performance, periodic quadrocopter maneuvers,” J. Mechatronics, vol. 24, no. 8, pp. 954–965, 2014.
- PID, LQR and LQR-PID on a quadcopter platform, Lucas M. Argentim et al. (2013)
- Multi-Agent Testbed development, modelling and control of Quadrotor UAVs. p.p. 27-31, KTH Thesis. (2012)
- Comparison of PID and LQR controllers on a quadrotor helicopter, Demet Canpolat Tosun et al. (2015)
- LQR- MIT Reference, A Good Theoritical Proof, MIT.
- Visual-Inertial-Aided Navigation for High-Dynamic Motion in Built Environments Without Initial Conditions: Sukkarieh's first paper on VIO using a Pre-Integrated factor. Code
- IMU Preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation: Scaramuzza's VIO paper for pre-integration on Manifold, used in project Tango. Code
- The Battle for Filter Supremacy: A Comparative Study of the Multi-State Constraint Kalman Filter and the Sliding Window Filter: Lee Clement's awesome comparsion paper. Code
- Iterated extended Kalman filter based visual-inertial odometry using direct photometric feedback: ETH-Z ROVIO paper. Works like a charm. Code
- MSCKF based Monocular VIO: Kostas' Implementation of MSKF based monocular VIO used in EVIO paper. Code
- VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator: Shaojie's awesome VIO code. Code
- A Benchmark Comparison of Monocular Visual-Inertial Odometry Algorithms for Flying Robots: Scaramuzza's great comparison of SVO, MSCKF, OKVIS, ROVIO and VINS on different computers: Laptop, Intel NUC, Up Board and ODROID.