Materials Matter: Investigating Functional Advantages of Bio-Inspired Materials via Simulated Robotic Hopping
Andrew K. Schulz* · Ayah G. Ahmad* · Maegan Tucker* ·
* designates equivalent contributions to this GitHub repository.
This code was tested with:
- Ubuntu 22.4
- CUDA 11.8
- python 3.9
This repository provides a simulation environment for one-legged hopping that models physical material designs. This repository is intended to accompany our ICRA 2025 submission titled ''Materials Matter: Investigating Functional Advantages of Bio-Inspired Materials via Simulated Robotic Hopping''.
Our framework utilizes the python bindings of MuJoCo (documentation: https://mujoco.readthedocs.io/en/stable/python.html) To install this on your computer, you should only have to run the following
pip install mujoco
Note: DO NOT try and install mujoco_py, this is an outdated and no-longer-maintained version of mujoco python.
After installing mujoco, you can test your installation by opening the standalone app:
python -m mujoco.viewer
To run the first set of experiments, run the python script run_experiment_one.py:
python run_experiment_one.py
To run the second set of experiments, run the python script run_experiment_two.py:
python run_experiment_two.py
To run the third set of experiments, run the python script run_experiment_three.py:
python run_experiment_three.py
To obtain the heatmap depicted in Figure 4, run the python script run_experiment_simtimes.py:
python run_experiment_simtimes.py
Lastly, to simulate a single instance of one-legged hopping, run the python script test_hopping.py
python test_hopping
Within this script, you can select which behavior you would like to run, and which xml you would like to utilize.
@misc{schulz_materials_2024,
title = {Materials Matter: Investigating Functional Advantages of Bio-Inspired Materials via Simulated Robotic Hopping},
author = {Schulz, Andrew K. and Ahmad, Ayah G. and Tucker, Maegan},
year = {2024},
}
See the LICENSE file for more information.
The authors would like to acknowledge that much of this work is possible with the help of several different repositories including the Mujoco XML Reference.
The authors thank the Alexander von Humboldt Foundation and International Max Planck Research School for Intelligent Systems, IMPRS-IS for supporting AKS. The authors thank the authors of the BITE paper for this Readme template. Thanks to Katherine J. Kuchenbecker for the support.
This code repository was implemented by Andrew Schulz, Ayah Ahmad, and Maegan Tucker in collaboration between The Dynamic Mobility Group at Georgia Tech and the Haptic Intelligence Department at the Max Planck Institute for Intelligent Systems - Stuttgart.
Give a ⭐ if you like our work.