Sorotraj: Generate trajectories for soft robots
Sorotraj allows you to generate trajectory functions to control soft robots. Trajectories are defined in a simple, human-readable yaml file, and are designed for compatibillity with both Ctrl-P pressure controllers (for real-world soft robots) and SoMo simulations (for virtual soft robots).
Table of Contents
Quick Install
pip install sorotraj
Explore the Examples
Check out the Examples, or run any of the files in the examples folder. The “Build One Trajectory” example is a great place to start!
Links
Documentation: Read the Docs
pip install: View on PyPi
Source code: Github
Contact
If you have questions, or if you’ve done something interesting with this package, get in touch with Clark Teeple, or the Harvard Microrobotics Lab!
If you find a problem or want something added to the library, open an issue on Github.
Used In…
Sorotraj has enabled several published works:
References
- graule2020somo
Moritz A. Graule, Clark B Teeple, Thomas P McCarthy, Randall C St. Louis, Grace R Kim, and Robert J Wood. Somo: fast and accurate simulation of continuum robots in complex environments. In IEEE International Conference on Intelligent Robots and Systems (IROS). IEEE, 2021.
- teeple2021active
Clark B Teeple, Grace R Kim, Moritz A. Graule, and Robert J Wood. An active palm enhances dexterity for soft robotic in-hand manipulation. In IEEE International Conference on Robotics and Automation (ICRA), volume, 11790–11796. 2021. doi:10.1109/ICRA48506.2021.9562049.
- teeple2021arrangement
Clark B Teeple, Randall C. St. Louis, Moritz A. Graule, and Robert J Wood. The role of digit arrangement in soft robotic in-hand manipulation. In IEEE International Conference on Intelligent Robots and Systems (IROS). IEEE, 2021.