3 papers
cs.RO2026
CAIMAN: Causal Action Influence Detection for Sample-efficient Loco-manipulation
Yuanchen Yuan, Jin Cheng, Núria Armengol Urpà +1
Enabling legged robots to perform non-prehensile loco-manipulation is crucial for enhancing their versatility. Learning behaviors such as whole-body object pushing often requires s…
cs.LG2025
Epistemically-guided forward-backward exploration
Núria Armengol UrpÃ, Marin Vlastelica, Georg Martius +1
Zero-shot reinforcement learning is necessary for extracting optimal policies in absence of concrete rewards for fast adaptation to future problem settings. Forward-backward repres…
cs.LG2024
Causal Action Influence Aware Counterfactual Data Augmentation
Núria Armengol UrpÃ, Marco Bagatella, Marin Vlastelica +1
Offline data are both valuable and practical resources for teaching robots complex behaviors. Ideally, learning agents should not be constrained by the scarcity of available demons…