A modified benchmark for designing and controlling 2D Voxel-based Soft Robots
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Updated
Nov 18, 2023 - Python
A modified benchmark for designing and controlling 2D Voxel-based Soft Robots
Robot evolution framework for the Triangle of Life project
Repository replicating the design- and behaviour-adaptation algorithm using reinforcement learning algorithm presented in the paper " Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning"
A universal supervisor controller and ER suite for Webots that can be adapted to any wheeled robot morphology with ease. The project is also setup to allow for easy Reinforcement Learning experimentation with some select algorithms (CMA-ES, Novlty Search, MAP-Elites) and neural networks (fixed and recurrent).
This is the official repository for the GECCO (Genetic and Evolutionary Computation Conference, 2022) paper "A Comparative Analysis on Genome Pleiotropy for Evolved Soft Robots". This repository hosts all the code necessary to replicate the experiments. This work was carried out at Ghent University IDLab-AIRO.
This is the official repository for the ALIFE paper "Shape Change and Control of Pressure-based Soft Agents" and its Artificial Life journal extension "Pressure-based Soft Agents".
Evolutionary Robotics with Gramatical Evolution for Dissertation
Repository containing results and the algorithms described in the article: https://periodicos.ufsm.br/coming/article/view/85256
This is the official repository for the GECCO paper "Morphology Choice Affects the Evolution of Affordance Detection in Robots".
This work was carried out at Ghent University (IDLab-AIRO), in collaboration with the Vrije Universiteit Brussel (R&MM).
Python API with evolutionary computation and reinforcement learning algorithms for Khepera simulation engine
Evolutionary Computing Research Project
SCOPE uses the Discrete Cosine Transform to compress high-dimensional pose data for hexapod control. By reducing input size from 2700 to 54, it enables faster and more effective evolutionary learning—achieving a 20% performance boost in gait generation.
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