5 papers
Neuro-Symbolic Predicate Learning for Semantic Safe Robot Control
Zihan Ye, Jiayi Liu, Puze Liu +4
As robots are increasingly deployed in everyday environments, ensuring their safety has become a central challenge. Existing methods often encode safety requirements as opaque math…
GORDON: Graph-based Object-centric Rewards for Decomposition of Long-Horizon Manipulation
Andrea Protopapa, Davide Buoso, Francesca Pistilli +2
Learning long-horizon manipulation skills with reinforcement learning remains challenging due to the complexity of reward design, the limited guidance of sparse rewards, and the hi…
Continual Learning Should Move Beyond Incremental Classification
Rupert Mitchell, Antonio Alliegro, Raffaello Camoriano +17
Continual learning (CL) is the sub-field of machine learning concerned with accumulating knowledge in dynamic environments. So far, CL research has mainly focused on incremental cl…
Learning to Reason over Scene Graphs: A Case Study of Finetuning GPT-2 into a Robot Language Model for Grounded Task Planning
Georgia Chalvatzaki, Ali Younes, Daljeet Nandha +3
Long-horizon task planning is essential for the development of intelligent assistive and service robots. In this work, we investigate the applicability of a smaller class of large…
Entropy-driven Unsupervised Keypoint Representation Learning in Videos
Ali Younes, Simone Schaub-Meyer, Georgia Chalvatzaki
Extracting informative representations from videos is fundamental for effectively learning various downstream tasks. We present a novel approach for unsupervised learning of meanin…