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.