mathworks-robotics /
awesome-matlab-robotics
This is a list of awesome demos, tutorials, utilities and overall resources for the robotics community that use MATLAB and Simulink.
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SihaoSun / repository
This is a minimal repository containing the Matlab / Simulink to test a quadrotor subjected to single / double rotor failures, the incremental-nonlinear-dynamic-inversion controller.
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Matlab / Simulink 2020a
Communication Toolbox
DSP System Toolbox
Robotics Toolbox
This is a minimal repository containing the Matlab / Simulink file, to simulate a quadrotor subjected to single / double rotor failures, using the incremental-nonlinear-dynamic-inversion controller proposed in
S. Sun, X. Wang, Q. Chu and C. d. Visser, "Incremental Nonlinear Fault-Tolerant Control of a Quadrotor With Complete Loss of Two Opposing Rotors," in IEEE Transactions on Robotics, doi: 10.1109/TRO.2020.3010626.
If you use this code in an academic context, please cite
@article{sun2020incremental,
title={Incremental nonlinear fault-tolerant control of a quadrotor with complete loss of two opposing rotors},
author={Sun, Sihao and Wang, Xuerui and Chu, Qiping and de Visser, Coen},
journal={IEEE Transactions on Robotics},
volume={37},
number={1},
pages={116--130},
year={2020},
publisher={IEEE}
}
run.m is the main script to run the simulation, after loading necessary simulation and control parameters defined in simParams.m & controlParams.m respectively. The high-level simulation archetecture is given in frame.slx file, where one can design the position + yaw command. The flight controller is given in controls.slx, and the 6Dof simulator is given in droneSim.slx file. visualize.slx contains the visualization block.
The innovation of this research, is to solve quadrotor fault-tolerant control problem using the Incremental-Nonlinear-Dynamic-Inversion (INDI) method. One can simply test it by directly running the simulation (run run.m file).
In controlParams.m file, one can select swtching off which one or two propellers by changing par.fail_id. If par.DRF_enable is set as 1, then both the rotor of the given index and the rotor on its opposite side are switched off.
Initial condition can be changed in the simParams.m file.
Input command can be designed in the frame.slx file.
To test your own controller with the given simulation, simply replace the content in controls.slx.
Selected from shared topics, language and repository description—not editorial ratings.
mathworks-robotics /
This is a list of awesome demos, tutorials, utilities and overall resources for the robotics community that use MATLAB and Simulink.
78/100 healthUSNavalResearchLaboratory /
This is a collection of Matlab functions that are useful in the development of target tracking algorithms.
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This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.
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This is a Matlab lesson design for vehicle detection and recognition. Using cifar-10Net to training a RCNN, and finetune AlexNet to classify. Thanks to Cars Dataset:http://ai.stanford.edu/~jkrause/cars/car_dataset.html
49/100 healthtomcattiger1230 /
This repository is an implementation of the work from Mohamed W. Mehrez. I convert the original code in MATLAB to the Python
64/100 health