On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme
Conference Proceeding
Goff, L. K. L., & Hart, E. (2021)
On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme. In GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion (1498-1502). https://doi.org/10.1145/3449726.3463156
We investigate a hierarchical scheme for the joint optimisation of robot bodies and controllers in a complex morphological space. An evolutionary algorithm optimises body-plan...
Evolution of Diverse, Manufacturable Robot Body Plans
Conference Proceeding
Buchanan, E., Le Goff, L., Hart, E., Eiben, A. E., De Carlo, M., Li, W., …Tyrrell, A. M. (2020)
Evolution of Diverse, Manufacturable Robot Body Plans. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI) (2132-2139). https://doi.org/10.1109/SSCI47803.2020.9308434
Advances in rapid prototyping have opened up new avenues of research within Evolutionary Robotics in which not only controllers but also the body plans (morphologies) of robot...
Hardware Design for Autonomous Robot Evolution
Conference Proceeding
Hale, M. F., Angus, M., Buchanan, E., Li, W., Woolley, R., Le Goff, L. K., …Tyrrell, A. M. (2020)
Hardware Design for Autonomous Robot Evolution. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI) (2140-2147). https://doi.org/10.1109/SSCI47803.2020.9308204
The long term goal of the Autonomous Robot Evolution (ARE) project is to create populations of physical robots, in which both the controllers and body plans are evolved. The t...
On Pros and Cons of Evolving Topologies with Novelty Search
Conference Proceeding
Le Goff, L. K., Hart, E., Coninx, A., & Doncieux, S. (2020)
On Pros and Cons of Evolving Topologies with Novelty Search. In ALIFE 2020: The 2020 Conference on Artificial Life. , (423-431). https://doi.org/10.1162/isal_a_00291
Novelty search was proposed as a means of circumventing deception and providing selective pressure towards novel behaviours to provide a path towards open-ended evolution. Ini...
Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation
Conference Proceeding
Le Goff, L. K., Buchanan, E., Hart, E., Eiben, A. E., Li, W., De Carlo, M., …Tyrrell, A. M. (2020)
Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation. In ALIFE 2020: The 2020 Conference on Artificial Life. , (432-440). https://doi.org/10.1162/isal_a_00299
In evolutionary robot systems where morphologies and controllers of real robots are simultaneously evolved, it is clear that there is likely to be requirements to refine the i...