Collective robotics through real-time entrainment of evolved dynamical systems
The master branch is updated continuously. Branches are made for reproduction of paper-specific data.
Clone the repository. To enable the Unity simulations (currently Linux only), create a Python virtual environment using CPG/requirements.txt.
This is a Python-only implementation that evolves disembodied CPGs directly for flexible periods. Filters are evolved for period matching.
Szorkovszky A, Veenstra F, and Glette K (2022) in 2022 International Joint Conference on Neural Networks (IJCNN)
https://doi.org/10.1109/IJCNN55064.2022.9891909
This is a Python+Unity implementation. CPGs are evolved for stable backwards+forward+accelerating motion as control parameters are swept. Filters are evolved for period matching.
Szorkovszky A, Veenstra F and Glette K (2023) Bioinspiration and Biomimetics 18:046020
https://doi.org/10.1088/1748-3190/ace017
This is a Python+Unity implementation. Short-legged quadruped agents from Paper2 are tested with a wide range of pulse inputs and musical excerpts.
Szorkovszky A, Veenstra F, Lartillot O, Jensenius AR and Glette K (2023), in Proceedings of the Sound and Music Conference 2023, pp 283-288
https://zenodo.org/doi/10.5281/zenodo.10060970
This is a Python+Unity implementation. Short-legged quadruped agents from Paper2 and newly evolved hexapods are run in teacher-learner pairs. A quasi-Hebbian process is used to turn synchronized gaits into autonomous gaits.
Szorkovszky A, Veenstra F and Glette K (2023). Frontiers in Robotics and AI, 10:1232708.