Outputs (2)

Quality-Diversity Optimisation on a Physical Robot Through Dynamics-Aware and Reset-Free Learning (2023)
Presentation / Conference Contribution
Smith, S. C., Lim, B., Janmohamed, H., & Cully, A. (2023, July). Quality-Diversity Optimisation on a Physical Robot Through Dynamics-Aware and Reset-Free Learning. Presented at Genetic and Evolutionary Computation Conference Companion (GECCO 2023 Companion), Lisbon

Learning algorithms, like Quality-Diversity (QD), can be used to acquire repertoires of diverse robotics skills. This learning is commonly done via computer simulation due to the large number of evaluations required. However, training in a virtual en... Read More about Quality-Diversity Optimisation on a Physical Robot Through Dynamics-Aware and Reset-Free Learning.

Online Damage Recovery for Physical Robots with Hierarchical Quality-Diversity (2023)
Journal Article
Allard, M., Smith, S. C., Chatzilygeroudis, K., Lim, B., & Cully, A. (2023). Online Damage Recovery for Physical Robots with Hierarchical Quality-Diversity. ACM Transactions on Evolutionary Learning and Optimization, 3(2), Article 6. https://doi.org/10.1145/3596912

In real-world environments, robots need to be resilient to damages and robust to unforeseen scenarios. Quality-Diversity (QD) algorithms have been successfully used to make robots adapt to damages in seconds by leveraging a diverse set of learned ski... Read More about Online Damage Recovery for Physical Robots with Hierarchical Quality-Diversity.