Accompanying code for the paper Learning Stable and Barrier-Certified Systems for Robotic Tasks: A Compositional Approach by Ali Aminzadeh1,*, Martin Schonger2,*, Hugo T. M. Kussaba2, Ahmed Abdelrahman2, Abdalla Swikir2, Abolfazl Lavaei1, and Sami Haddadin2, currently under review.
1School of Computing, Newcastle University, UK.
2Munich Institute of Robotics and Machine Intelligence (MIRMI), Technical University of Munich (TUM), Germany. Abdalla Swikir is also with Omar Al-Mukhtar University (OMU), Albaida, Libya.
*Shared first authorship.
Install MATLAB (tested with R2023a).
Install the MathWorks toolboxes Robotics System Toolbox, Signal Processing Toolbox, and Symbolic Math Toolbox.
Install the third party tools YALMIP (version 20230622; changed sdisplay precision in PATH/TO/yalmip/extras/sdisplay.m LOCs 311, 313, 317, and 319 from 12 to 128), PENBMI (version 2.1), and GUROBI (version 10.0.2 build v10.0.2rc0 (win64)).
Note Make sure that the non-toolbox paths are before/on top of the toolbox paths.
Open the abcc-ds folder in MATLAB.
Configure the desired experiments in main.m and run this script.
Check the output folder for results and logs.
(Optionally, recreate the plots from the paper with plotting/generate_plots_iros.m, and the animations from the video with plotting/generate_plots_video_iros.m.)
This software was created as part of Martin Schonger's master's thesis in Computer Science at the Technical University of Munich's (TUM) School of Computation, Information and Technology (CIT).
Copyright © 2024 Martin Schonger
This software is licensed under the GPLv3.