12 citations · 21 across the 5 of their papers we have counts for
4 papers · 1 filter
Online Damage Recovery for Physical Robots with Hierarchical Quality-Diversity
Maxime Allard, Simón C. Smith, Konstantinos Chatzilygeroudis +2
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…
Hierarchical Quality-Diversity for Online Damage Recovery
Maxime Allard, Simón C. Smith, Konstantinos Chatzilygeroudis +1
Adaptation capabilities, like damage recovery, are crucial for the deployment of robots in complex environments. Several works have demonstrated that using repertoires of pre-train…
Attainment Regions in Feature-Parameter Space for High-Level Debugging in Autonomous Robots
Simón C. Smith, Subramanian Ramamoorthy
Understanding a controller's performance in different scenarios is crucial for robots that are going to be deployed in safety-critical tasks. If we do not have a model of the dynam…
Semi-supervised Learning From Demonstration Through Program Synthesis: An Inspection Robot Case Study
Simón C. Smith, Subramanian Ramamoorthy
Semi-supervised learning improves the performance of supervised machine learning by leveraging methods from unsupervised learning to extract information not explicitly available in…