This repository contains the code for Post-capture detumble trajectory stabilization for robotic active debris removal
The PostCapDetumbleTrajectory class is provided in the file PostCapDetumbleTrajOpt.py. The TVLQRTrajectoryStabilizer class is provided in the file TrajectoryStabilizationTVLQR.py. Example use of these classes can be seen in the application folder asr_paper_system.
Animated GIF of the detumble simulation with TVLQR Controller:
Base and Joint Velocities and Torques During Detumble:
The repository has the following dependencies:
- numpy
- Drake (https://drake.mit.edu/) (Install via apt or tarball as SNOPT is not installed via pip and this solver is used for trajectory optimization)
- toml
- matplotlib
- pickle
asr_paper_system: Contains the code for the system used in the following paper: Vyas, S., Maywald, L., Kumar, S., Jankovic, M., Mueller, A. and Kirchner, F., 2022. Post-capture detumble trajectory stabilization for robotic active debris removal. Advances in Space Research.
DOI: 10.1016/j.asr.2022.09.033
Bibtex:
@article{VYAS2022,
dimensions = {true},
title = {Post-capture detumble trajectory stabilization for robotic active debris removal},
journal = {Advances in Space Research},
year = {2022},
issn = {0273-1177},
doi = {10.1016/j.asr.2022.09.033},
url = {https://www.sciencedirect.com/science/article/pii/S0273117722008742},
author = {Vyas, Shubham and Maywald, Lasse and Kumar, Shivesh and Jankovic, Marko and Mueller, Andreas and Kirchner, Frank},
keywords = {Active debris removal, Space robotics, Trajectory stabilization},
month = sep
}
This research was conducted within Stardust Reloaded project which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813644.